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The April 2010 Deepwater Horizon drilling unit explosion at the Macondo oil well resulted in the release of approximately 779 million l of oil into the Gulf of Mexico. As part of the response effort to break up oil slicks on the water’s surface, 6.81 million l of chemical dispersants COREXIT™ EC9500A and COREXIT™ EC9527A were applied by plane or vessel or injected near the seabed. The GuLF Long-term Follow-up Study is investigating possible adverse health effects of workers involved in the oil spill response and clean-up (OSRC). In this paper, we describe potential dispersant-related air concentrations generated from aerial spraying of dispersants to provide insight as to what concentrations OSRC workers may have been exposed under worst-case conditions. Personal exposure measurement data were not collected. Modeling, therefore, was conducted to estimate airborne concentrations of total aerosol to COREXIT™ EC9527A and EC9500A. Using the AgDISP model, we estimated air concentrations to dispersant total aerosols, defined as all components of the dispersant including active ingredients, surfactants, and water, resulting from aerial and vessel applications, as average 1-h and 2-min concentrations. For comparison, 1-h air concentrations associated with aerial spraying were estimated using another model, AERMOD. At 152 m horizontal to the flight path, average 1-h total aerosol concentrations associated with aerial applications were estimated to be as high as 49.3 µg m−3 (9527A) and 45.4 µg m−3 (9500A), and both decreased with increased distance from the flight line. The estimates for spraying 9500A from vessels indicated that total aerosol concentrations were potentially as high as 0.33 µg m−3 at 10 m from the nozzles. These results suggest that personal exposures to dispersant aerosols were negligible.

The GuLF STUDY is investigating health outcomes associated with oil spill-related chemical exposures among workers involved in the spill response and clean-up following the Deepwater Horizon disaster. Due to the lack of dermal exposure measurements, we estimated dermal exposures using a deterministic model, which we customized from a previously published model. Workers provided information on the frequency of contact with oil, tar, chemical dispersants applied to the oil spill and sea water, as well as the use of protective equipment, by job/activity/task. Professional judgment by industrial hygienists served as a source of information for other model variables. The model estimated dermal exposures to total hydrocarbons (THC), benzene, ethylbenzene, toluene, xylene, n-hexane (BTEX-H), polycyclic aromatic hydrocarbons (PAHs), and dispersants in GuLF DREAM units (GDUs). Arithmetic means (AMs) of THC exposure estimates across study participants ranged from 0.9) for most of the substances in oil but were lower for some of the substances in tar. These data were linked to the study participants to allow investigation of adverse health effects that may be related to dermal exposures.

Objectives Our objectives were to (i) determine correlations between measurements of THC and of BTEX-H, (ii) apply these linear relationships to predict BTEX-H from measured THC, (iii) use these correlations as informative priors in Bayesian analyses to estimate exposures. Methods We used a Bayesian left-censored bivariate framework for all 3 objectives. First, we modeled the relationships (i.e. correlations) between THC and each BTEX-H chemical for various overarching groups of measurements using linear regression to determine if correlations derived from linear relationships differed by various exposure determinants. We then used the same linear regression relationships to predict (or impute) BTEX-H measurements from THC when only THC measurements were available. Finally, we used the same linear relationships as priors for the final exposure models that used real and predicted data to develop exposure estimate statistics for each individual exposure group. Results Correlations between measurements of THC and each of the BTEX-H chemicals (n = 120 for each of BTEX, 36 for n-hexane) differed substantially by area of the Gulf of Mexico and by time period that reflected different oil-spill related exposure opportunities. The correlations generally exceeded 0.5. Use of regression relationships to impute missing data resulted in the addition of >23 000 n-hexane and 541 observations for each of BTEX. The relationships were then used as priors for the calculation of exposure statistics while accounting for censored measurement data. Conclusions Taking advantage of observed relationships between THC and BTEX-H allowed us to develop robust exposure estimates where a large amount of data were missing, strengthening our exposure estimation process for the epidemiologic study.

The GuLF Long-term Follow-up Study (GuLF STUDY) is investigating potential adverse health effects of workers involved in the Deepwater Horizon (DWH) oil spill response and cleanup (OSRC). Over 93% of the 160 000 personal air measurements taken on OSRC workers were below the limit of detection (LOD), as reported by the analytic labs. At this high level of censoring, our ability to develop exposure estimates was limited. The primary objective here was to reduce the number of measurements below the labs’ reported LODs to reflect the analytic methods’ true LODs, thereby facilitating the use of a relatively unbiased and precise Bayesian method to develop exposure estimates for study exposure groups (EGs). The estimates informed a job-exposure matrix to characterize exposure of study participants. A second objective was to develop descriptive statistics for relevant EGs that did not meet the Bayesian criteria of sample size ≥5 and censoring ≤80% to achieve the aforementioned level of bias and precision. One of the analytic labs recalculated the measurements using the analytic method’s LOD; the second lab provided raw analytical data, allowing us to recalculate the data values that fell between the originally reported LOD and the analytical method’s LOD. We developed rules for developing Bayesian estimates for EGs with >80% censoring. The remaining EGs were 100% censored. An order-based statistical method (OBSM) was developed to estimate exposures that considered the number of measurements, geometric standard deviation, and average LOD of the censored samples for N ≥ 20. For N < 20, substitution of ½ of the LOD was assigned. Recalculation of the measurements lowered overall censoring from 93.2 to 60.5% and of the THC measurements, from 83.1 to 11.2%. A total of 71% of the EGs met the ≤15% relative bias and 80% but enough non-censored measurements to apply Bayesian methods. We used the OBSM for 3% of the estimates and the simple substitution method for 11%. The methods presented here substantially reduced the degree of censoring in the dataset and increased the number of EGs meeting our Bayesian method’s desired performance goal. The OBSM allowed for a systematic and consistent approach impacting only the lowest of the exposure estimates. This approach should be considered when dealing with highly censored datasets.

Background The 2010 Deepwater Horizon (DWH) oil spill involved thousands of workers and volunteers to mitigate the oil release and clean-up after the spill. Health concerns for these participants led to the initiation of a prospective epidemiological study (GuLF STUDY) to investigate potential adverse health outcomes associated with the oil spill response and clean-up (OSRC). Characterizing the chemical exposures of the OSRC workers was an essential component of the study. Workers on the four oil rig vessels mitigating the spill and located within a 1852 m (1 nautical mile) radius of the damaged wellhead [the Discoverer Enterprise (Enterprise), the Development Driller II (DDII), the Development Driller III (DDIII), and the HelixQ4000] had some of the greatest potential for chemical exposures. Objectives The aim of this paper is to characterize potential personal chemical exposures via the inhalation route for workers on those four rig vessels. Specifically, we presented our methodology and descriptive statistics of exposure estimates for total hydrocarbons (THCs), benzene, toluene, ethylbenzene, xylene, and n-hexane (BTEX-H) for various job groups to develop exposure groups for the GuLF STUDY cohort. Methods Using descriptive information associated with the measurements taken on various jobs on these rig vessels and with job titles from study participant responses to the study questionnaire, job groups [unique job/rig/time period (TP) combinations] were developed to describe groups of workers with the same or closely related job titles. A total of 500 job groups were considered for estimation using the available 8139 personal measurements. We used a univariate Bayesian model to analyze the THC measurements and a bivariate Bayesian regression framework to jointly model the measurements of THC and each of the BTEX-H chemicals separately, both models taking into account the many measurements that were below the analytic limit of detection. Results Highest THC exposures occurred in TP1a and TP1b, which was before the well was mechanically capped. The posterior medians of the arithmetic mean (AM) ranged from 0.11 ppm (‘Inside/Other’, TP1b, DDII; and ‘Driller’, TP3, DDII) to 14.67 ppm (‘Methanol Operations’, TP1b, Enterprise). There were statistical differences between the THC AMs by broad job groups, rigs, and time periods. The AMs for BTEX-H were generally about two to three orders of magnitude lower than the THC AMs, with benzene and ethylbenzene measurements being highly censored. Conclusions Our results add new insights to the limited literature on exposures associated with oil spill responses and support the current epidemiologic investigation of potential adverse health effects of the oil spill.

The GuLF Study is investigating adverse health effects from work on the response and clean-up after the Deepwater Horizon explosion and oil release. An essential and necessary component of that study was the exposure assessment. Bayesian statistical methods and over 135 000 measurements of total hydrocarbons (THC), benzene, ethylbenzene, toluene, xylene, and n-hexane (BTEX-H) were used to estimate inhalation exposures to these chemicals for >3400 exposure groups (EGs) formed from three exposure determinants: job/activity/task, location, and time period. Recognized deterministic models were used to estimate airborne exposures to particulate matter sized 2.5 µm or less (PM2.5) and dispersant aerosols and vapors. Dermal exposures were estimated for these same oil-related substances using a model modified especially for this study from a previously published model. Exposures to oil mist were assessed using professional judgment. Estimated daily THC arithmetic means (AMs) were in the low ppm range (

In the GuLF Study, a study investigating possible adverse health effects associated with work on the oil spill response and clean-up (OSRC) following the Deepwater Horizon disaster in the Gulf of Mexico, we used a job-exposure matrix (JEM) approach to estimate exposures. The JEM linked interview responses of study participants to measurement data through exposure groups (EGs). Here we describe a systematic process used to develop transparent and precise EGs that allowed characterization of exposure levels among the large number of OSRC activities performed across the Gulf of Mexico over time and space. EGs were identified by exposure determinants available to us in our measurement database, from a substantial body of other spill-related information, and from responses provided by study participants in a detailed interview. These determinants included: job/activity/task, vessel and type of vessel, weathering of the released oil, area of the Gulf of Mexico, Gulf coast state, and time period. Over 3000 EGs were developed for inhalation exposure and applied to each of 6 JEMs of oil-related substances (total hydrocarbons, benzene, toluene, ethylbenzene, total xylene, and n-hexane). Subsets of those EGs were used for characterization of exposures to dispersants, particulate matter, and oil mist. The EGs allowed assignment to study participants of exposure estimates developed from measurement data or from estimation models through linkage in the JEM for the investigation of exposure-response relationships.

Objective To examine the frequency of, and risk factors for, disease flare following COVID-19 vaccination in patients with systemic rheumatic disease (SRD). Methods An international study was conducted from 2 April to 16 August 2021, using an online survey of 5619 adults with SRD for adverse events following COVID-19 vaccination, including flares of disease requiring a change in treatment. We examined risk factors identified a priori based on published associations with SRD activity and SARS-CoV-2 severity, including demographics, SRD type, comorbidities, vaccine type, cessation of immunosuppressive medications around vaccination and history of reactions to non-COVID-19 vaccines, using multivariable logistic regression. Results Flares requiring a change in treatment following COVID-19 vaccination were reported by 4.9% of patients. Compared with rheumatoid arthritis, certain SRD, including systemic lupus erythematosus (OR 1.51, 95% CI 1.03, 2.20), psoriatic arthritis (OR 1.95, 95% CI 1.20, 3.18) and polymyalgia rheumatica (OR 1.94, 95% CI 1.08, 2.48) were associated with higher odds of flare, while idiopathic inflammatory myopathies were associated with lower odds for flare (OR 0.54, 95% CI 0.31–0.96). The Oxford-AstraZeneca vaccine was associated with higher odds of flare relative to the Pfizer-BioNTech vaccine (OR 1.44, 95% CI 1.07, 1.95), as were a prior reaction to a non-COVID-19 vaccine (OR 2.50, 95% CI 1.76, 3.54) and female sex (OR 2.71, 95% CI 1.55, 4.72). Conclusion SRD flares requiring changes in treatment following COVID-19 vaccination were uncommon in this large international study. Several potential risk factors, as well as differences by disease type, warrant further examination in prospective cohorts.

Background: During the 2010 Deepwater Horizon (DWH) disaster, controlled burning was conducted to remove oil from the water. Workers near combustion sites were potentially exposed to increased fine particulate matter [with aerodynamic diameter ≤2.5μm (PM2.5)] levels. Exposure to PM2.5 has been linked to decreased lung function, but to our knowledge, no study has examined exposure encountered in an oil spill cleanup. Objective: We investigated the association between estimated PM2.5 only from burning/flaring of oil/gas and lung function measured 1–3 y after the DWH disaster. Methods: We included workers who participated in response and cleanup activities on the water during the DWH disaster and had lung function measured at a subsequent home visit (n=2,316). PM2.5 concentrations were estimated using a Gaussian plume dispersion model and linked to work histories via a job-exposure matrix. We evaluated forced expiratory volume in 1 s (FEV1; milliliters), forced vital capacity (FVC; milliliters), and their ratio (FEV1/FVC; %) in relation to average and cumulative daily maximum exposures using multivariable linear regressions. Results: We observed significant exposure–response trends associating higher cumulative daily maximum PM2.5 exposure with lower FEV1 (p-trend=0.04) and FEV1/FVC (p-trend=0.01). In comparison with the referent group (workers not involved in or near the burning), those with higher cumulative exposures had lower FEV1 [−166.8mL, 95% confidence interval (CI): −337.3, 3.7] and FEV1/FVC (−1.7, 95% CI: −3.6, 0.2). We also saw nonsignificant reductions in FVC (high vs. referent: −120.9, 95% CI: −319.4, 77.6; p-trend=0.36). Similar associations were seen for average daily maximum PM2.5 exposure. Inverse associations were also observed in analyses stratified by smoking and time from exposure to spirometry and when we restricted to workers without prespill lung disease. Conclusions: Among oil spill workers, exposure to PM2.5 specifically from controlled burning of oil/gas was associated with significantly lower FEV1 and FEV1/FVC when compared with workers not involved in burning. https://doi.org/10.1289/EHP8930

Harmonized language is essential to finding, sharing, and reusing large-scale, complex data. Gaps and barriers prevent the adoption of harmonized language approaches in environmental health sciences (EHS). To address this, the National Institute of Environmental Health Sciences and partners created the Environmental Health Language Collaborative (EHLC). The purpose of EHLC is to facilitate a community-driven effort to advance the development and adoption of harmonized language approaches in EHS. EHLC is a forum to pinpoint language harmonization gaps, to facilitate the development of, raise awareness of, and encourage the use of harmonization approaches and tools, and to develop new standards and recommendations. To ensure that EHLC’s focus and structure would be sustainable long-term and meet the needs of the field, EHLC launched an inaugural workshop in September 2021 focused on “Developing Sustainable Language Solutions” and “Building a Sustainable Community”. When the attendees were surveyed, 91% said harmonized language solutions would be of high value/benefit, and 60% agreed to continue contributing to EHLC efforts. Based on workshop discussions, future activities will focus on targeted collaborative use-case working groups in addition to offering education and training on ontologies, metadata, and standards, and developing an EHS language resource portal.

During the 2010 Deepwater Horizon (DWH) disaster, in-situ burning and flaring were conducted to remove oil from the water. Workers near combustion sites were potentially exposed to burning-related fine particulate matter (PMTo investigate the association between estimated PMWe included workers who participated in response and cleanup activities on the water during the DWH disaster (N = 9091). PMWe observed increased CHD hazard among workers with higher levels of average daily maximum exposure (low vs. referent: HR = 1.26, 95% CI: 0.93, 1.70; high vs. referent: HR = 2.11, 95% CI: 1.08, 4.12; per 10 μg/mAmong oil spill workers, exposure to PM

Even though the Deepwater Horizon oil spill response and clean-up (OSRC) had one of the largest exposure monitoring efforts of any oil spill, a number of exposure groups did not have sufficient personal data available or there were gaps in days measured to adequately characterize exposures for the GuLF STUDY, an epidemiologic study investigating the health of the OSRC workers. Area measurements were available from real-time air monitoring instruments and used to supplement the personal exposure measurements. Objectives The objective was to present a method that used real-time volatile organic compounds (VOCs) area measurements transformed to daily total hydrocarbons (THC) time-weighted averages (TWAs) to supplement THC personal full-shift measurements collected using passive charcoal badges. A second objective was to develop exposure statistics using these data for workers on vessels piloting remotely operated vehicle (ROV) vessels and other marine vessels (MVs) not at the job title level, but at the vessel level. Methods From hourly vessel averages derived from ~26 million real-time VOC measurements, we estimated full-shift VOC TWAs. Then, we determined the relationship between these TWAs and corresponding full-shift THC personal measurements taken on the same vessel-day. We used this relationship to convert the full-shift VOC measurements to full-shift ‘THC’ TWA estimates when no personal THC measurements existed on a vessel-day. We then calculated arithmetic means (AMs) and other statistics of THC exposures for each vessel. Results The VOC-derived estimates substantially supplemented the THC personal measurements, with the number of vessel-days for which we have exposure estimates increasing by ~60%. The estimates of the AMs are some of the highest observed in the GuLF STUDY. As expected, the AMs decreased over time, consistent with our findings on other vessels. Conclusions Despite the inherent limitations of using real-time area measurements, we were able to develop additional daily observations of personal THC exposures for workers on the ROV vessels and other MVs over time. The estimates likely resulted in more representative estimates of the AMs in the GuLF STUDY. The method used here can be applied in other occupational settings and industries for personal exposure estimation where large amounts of area measurements and more limited numbers of personal measurements are available.

The Deepwater Horizon (DWH) drilling unit explosion above the Macondo oil well on 20 April 2010 caused the release of approximately 4.9 million barrels (779 million L) of oil into the Gulf of Mexico. As part of a larger spill response and clean-up effort, approximately 1.84 million gallons (6.81 million L) of chemical dispersants COREXIT™ EC9500A and COREXIT™ EC9527A were applied to the resultant oil slicks through spraying on the water surface by plane and by vessel and through injection at the release source near the seabed. The GuLF STUDY is investigating the health effects of workers involved in the oil spill response and clean-up after the DWH explosion, and estimates of possible exposure to chemical dispersants were needed. Exposures were estimated to the volatile components of COREXIT™ EC9500A [petroleum distillates, hydrotreated light, and propylene glycol (PG)] and of COREXIT™ EC9527A [2-butoxyethanol (2-BE) and PG] using two of AIHA IHMOD2.0© mathematical modeling tools along with the dispersants’ chemical and physical properties. Monte Carlo simulations were used to reflect uncertainty in input parameters with both the two-box, constant emission model and the near and mid field plume model for indoor and outdoor activities, respectively. Possible exposure scenarios considered various evaporation rates, sizes of the dispersant pool, wind speeds, and ventilation rates. For the two-box model, mean near field exposure estimates to 2-BE ranged from 0.9 to 5.7 ppm, while mean far field estimated exposures ranged from 0.3 to 3.5 ppm. Estimates of mean near field plume model exposures ranged from 0.01 to 3.7 ppm at 2.5 ft from the source, and

Harmonized language is critical for helping researchers to find data, collecting scientific data to facilitate comparison, and performing pooled and meta-analyses. Using standard terms to link data to knowledge systems facilitates knowledge-driven analysis, allows for the use of biomedical knowledge bases for scientific interpretation and hypothesis generation, and increasingly supports artificial intelligence (AI) and machine learning. Due to the breadth of environmental health sciences (EHS) research and the continuous evolution in scientific methods, the gaps in standard terminologies, vocabularies, ontologies, and related tools hamper the capabilities to address large-scale, complex EHS research questions that require the integration of disparate data and knowledge sources. The results of prior workshops to advance a harmonized environmental health language demonstrate that future efforts should be sustained and grounded in scientific need. We describe a community initiative whose mission was to advance integrative environmental health sciences research via the development and adoption of a harmonized language. The products, outcomes, and recommendations developed and endorsed by this community are expected to enhance data collection and management efforts for NIEHS and the EHS community, making data more findable and interoperable. This initiative will provide a community of practice space to exchange information and expertise, be a coordination hub for identifying and prioritizing activities, and a collaboration platform for the development and adoption of semantic solutions. We encourage anyone interested in advancing this mission to engage in this community.

Research conducted in the wake of a disaster can provide information to help mitigate health consequences, support future recovery efforts, and improve resilience. However, a number of barriers have prevented time-sensitive research responses following previous disasters. Furthermore, large-scale disasters present their own special challenges due to the number of people exposed to disaster conditions, the number of groups engaged in disaster response, and the logistical challenges of rapidly planning and implementing a large study. In this case study, we illustrate the challenges in planning and conducting a large-scale post-disaster research study by drawing on our experience in establishing the Gulf Long-term Follow-up (GuLF) Study following the 2010 Deepwater Horizon disaster. We describe considerations in identifying at-risk populations and appropriate comparison groups, garnering support for the study from different stakeholders, obtaining timely scientific and ethics review, measuring and characterizing complex exposures, and addressing evolving community health concerns and unmet medical needs. We also describe the NIH Disaster Research Response (DR2) Program, which provides a suite of resources, including data collection tools, research protocols, institutional review board guidance, and training materials to enable the development and implementation of time-critical studies following disasters and public health emergencies. In describing our experiences related to the GuLF Study and the ongoing efforts through the NIH DR2 Program, we aim to help improve the timeliness, quality, and value of future disaster-related data collection and research studies.

Tens of thousands of individuals performed oil spill response and clean-up (OSRC) activities following the ‘Deepwater Horizon’ oil drilling rig explosion in 2010. Many were exposed to oil residues and dispersants. The US National Institute of Environmental Health Sciences assembled a cohort of nearly 33 000 workers to investigate potential adverse health effects of oil spill exposures. Estimates of dermal and inhalation exposure are required for those individuals. Ambient breathing-zone measurements taken at the time of the spill were used to estimate inhalation exposures for participants in the GuLF STUDY (Gulf Long-term Follow-up Study), but no dermal measurements were collected. Consequently, a modelling approach was used to estimate dermal exposures. We sought to modify DREAM (DeRmal Exposure Assessment Method) to optimize the model for assessing exposure to various oil spill-related substances and to incorporate advances in dermal exposure research. Each DREAM parameter was reviewed in the context of literature published since 2000 and modified where appropriate. To reflect the environment in which the OSRC work took place, the model treatment of evaporation was expanded to include vapour pressure and wind speed, and the effect of seawater on exposure was added. The modified model is called GuLF DREAM and exposure is estimated in GuLF DREAM units (GDU). An external validation to assess the performance of the model for oils, tars, and fuels was conducted using available published dermal wipe measurements of heavy fuel oil (HFO) and dermal hand wash measurements of asphalt. Overall, measured exposures had moderate correlations with GDU estimates (r = 0.59) with specific correlations of −0.48 for HFO and 0.68 for asphalt. The GuLF DREAM model described in this article has been used to generate dermal exposure estimates for the GuLF STUDY. Many of the updates made were generic, so the updated model may be useful for other dermal exposure scenarios.

Large spatial datasets are typically modelled through a small set of knot locations; often these locations are specified by the investigator by arbitrary criteria. Existing methods of estimating th...

A large body of research has linked disaster exposure to adverse mental and physical health outcomes. Few studies, however, have explored the cumulative impact of exposure to multiple disasters. Participants (N = 8,366) from the National Institute of Environmental Health Sciences Gulf Long-Term Follow-Up Study were classified as having been exposed to both, either, or neither Hurricane Katrina and the Deepwater Horizon oil spill (DHOS). Participants also reported on a range of mental and physical health symptoms. Logistic regression models found that participants who were exposed to both disasters had significantly higher odds of probable generalized anxiety disorder, odds ratio (OR) = 1.72, 95% CI [1.52, 1.96]; major depression, OR = 1.53, 95% CI [1.32, 1.77]; and posttraumatic stress disorder, OR = 2.51, 95% CI [2.03, 3.10], than participants who were exposed to only one disaster, ps < .001. Additionally, a linear regression model found that participants who were exposed to both disasters had significantly more physical health symptoms at the time of the spill than those who were exposed to only one disaster, B = 0.99, SE = .20, p < .001. The results indicate that cumulative disaster exposure confers enhanced risk for adverse mental and physical health outcomes. The findings demonstrate that screening for prior exposure among disaster-affected individuals might identify those at greatest risk for adverse health outcomes.

The NIEHS GuLF STUDY is an epidemiologic study of the health of workers who participated in the 2010 Deepwater Horizon oil spill response and clean-up effort. Even with a large database of approximately 28 000 personal samples that were analyzed for total hydrocarbons (THCs) and other oil-related chemicals, resulting in nearly 160 000 full-shift personal measurements, there were still exposure scenarios where the number of measurements was too limited to rigorously assess exposures. Also available were over 26 million volatile organic compounds (VOCs) area air measurements of approximately 1-min duration, collected from direct-reading instruments on 38 large vessels generally located near the leaking well. This paper presents a strategy for converting the VOC database into hourly average air concentrations by vessel as the first step of a larger process designed to use these data to supplement full-shift THC personal exposure measurements. We applied a Bayesian method to account for measurements with values below the analytic instrument’s limit of detection while processing the large database into average instrument-hour concentrations and then hourly concentrations across instruments on each day of measurement on each of the vessels. To illustrate this process, we present results on the drilling rig ship, the Discoverer Enterprise. The methods reduced the 26 million measurements to 21 900 hourly averages, which later contributed to the development of additional full-shift THC observations. The approach used here can be applied by occupational health professionals with large datasets of direct-reading instruments to better understand workplace exposures.

Background The Gulf Long-Term Follow-up (GuLF) Study is a prospective cohort study of health effects associated with oil spill response and clean-up following the 2010 Deepwater Horizon Disaster (DWH). As part of the study, spirometry testing of lung function was carried out in home visits across multiple states. Few studies have described factors associated with spirometry test failure in field-based settings. Objective Our objective was to identify what factors, if any, predict test failure among GuLF Study participants who completed spirometry testing in a non-traditional setting. Methods Trained examiners administered spirometry (May 2011–May 2013) to 10,019 participants living in US Gulf States (LA, MS, TX, AL, FL) using an Easy-on ultrasonic spirometer. We applied American Thoracic Society/European Respiratory Society quality criteria to determine quality test failure and identified factors predictive of failure using both a Stepwise and a LASSO model. We calculated odds ratios and 95% confidence intervals (CIs) for associations of selected factors with test failure. Results Among GuLF Study participants who conducted spirometry, self-reported African American/Black participants (OR: 1.39, 95% CI: 1.23,1.56); men (OR:1.61, 95% CI: 1.41,1.83); and those making less than $20,000 per year (OR: 1.45, 95% CI: 1.26,1.67) were more likely to fail quality testing, while those who were obese were less likely to fail (OR: 0.61, 95% CI: 0.42,0.89). Conclusion Field-based studies involving spirometry should identify and account for participant factors that may influence test failure. Coaching that is tailored to those less likely to have experience with spirometry may help reduce test failure rates.

The Deepwater Horizon oil spill response and clean-up (OSRC) involved over 9000 large and small vessels deployed in waters of the Gulf of Mexico across four states (Alabama, Florida, Louisiana, and Mississippi). For the GuLF STUDY, we developed exposure estimates of oil-related components for many work groups to capture a wide range of OSRC operations on these vessels, such as supporting the four rig vessels charged with stopping the spill at the wellhead; skimming oil; in situ burning of oil; absorbing and containing oil by boom; and environmental monitoring. Work groups were developed by: (i) vessel activity; (ii) location (area of the Gulf or state); and (iii) time period. Using Bayesian methods, we computed exposure estimates for these groups for: total hydrocarbons measured as total petroleum hydrocarbons (THC), benzene, toluene, ethylbenzene, xylene, and n-hexane (BTEX-H). Estimates of the arithmetic means for THC ranged from 0.10 ppm [95% credible interval (CI) 0.04, 0.38 ppm] in time periods 2 and 3 (16 July–30 September 2010) to 15.06 ppm (95% CI 10.74, 22.41 ppm) in time period 1a (22 April–15 May 2010). BTEX-H estimates were substantially lower (in the parts per billion range). Exposure levels generally fell over time and differed statistically by activity, location, and time for some groups. These exposure estimates have been used to develop job–exposure matrices for the GuLF STUDY.

In the wake of the Deepwater Horizon (DWH) oil spill, a number of government agencies, academic institutions, consultants, and nonprofit organizations conducted lab- and field-based research to understand the toxic effects of the oil. Lab testing was performed with a variety of fish, birds, turtles, and vertebrate cell lines (as well as invertebrates); field biologists conducted observations on fish, birds, turtles, and marine mammals; and epidemiologists carried out observational studies in humans. Eight years after the spill, scientists and resource managers held a workshop to summarize the similarities and differences in the effects of DWH oil on vertebrate taxa and to identify remaining gaps in our understanding of oil toxicity in wildlife and humans, building upon the cross-taxonomic synthesis initiated during the Natural Resource Damage Assessment. Across the studies, consistency was found in the types of toxic response observed in the different organisms. Impairment of stress responses and adrenal gland function, cardiotoxicity, immune system dysfunction, disruption of blood cells and their function, effects on locomotion, and oxidative damage were observed across taxa. This consistency suggests conservation in the mechanisms of action and disease pathogenesis. From a toxicological perspective, a logical progression of impacts was noted: from molecular and cellular effects that manifest as organ dysfunction, to systemic effects that compromise fitness, growth, reproductive potential, and survival. From a clinical perspective, adverse health effects from DWH oil spill exposure formed a suite of signs/symptomatic responses that at the highest doses/concentrations resulted in multi-organ system failure.

Socioeconomic status has been associated with cardiovascular disease risk factors. However, few studies have examined this relationship among populations in the US Gulf Coast region. We assessed neighborhood deprivation in relation to obesity and diabetes in 9,626 residents participating in the Gulf Long-Term Follow-Up Study (2011–present) who completed a home visit (2011–2013) with height, weight, waist, and hip measurements. Obesity was categorized as body mass index of at least 30, and diabetes was defined by doctor’s diagnosis or prescription medication. Participant home addresses were linked to an established Area Deprivation Index and categorized into 4 levels (1 = least deprived). In adjusted, modified Poisson regression models, participants with greatest deprivation were more likely to have obesity compared with those with least deprivation (adjusted prevalence ratio (aPR) = 1.21, 95% confidence interval (CI): 1.08, 1.35), central obesity (aPR = 1.11, 95% CI: 1.04, 1.19), and diabetes (aPR = 1.49, 95% CI: 1.03, 2.14). Repeated analyses among a subgroup of participants (n = 3,016) whose hemoglobin A1C values were measured 3 years later indicated the association with diabetes (defined as diagnosis, medications, or hemoglobin A1C ≥ 6.5) was similar (aPR = 1.46, 95% CI: 1.14, 1.86). Results suggest neighborhood deprivation is associated with obesity and diabetes in a US region with high baseline prevalence.

The GuLF STUDY, initiated by the National Institute of Environmental Health Sciences, is investigating the health effects among workers involved in the oil spill response and clean-up (OSRC) after the Deepwater Horizon (DWH) explosion in April 2010 in the Gulf of Mexico. Clean-up included in situ burning of oil on the water surface and flaring of gas and oil captured near the seabed and brought to the surface. We estimated emissions of PM2.5 and related pollutants resulting from these activities, as well as from engines of vessels working on the OSRC. PM2.5 emissions ranged from 30 to 1.33e6 kg per day and were generally uniform over time for the flares but highly episodic for the in situ burns. Hourly emissions from each source on every burn/flare day were used as inputs to the AERMOD model to develop average and maximum concentrations for 1-, 12-, and 24-h time periods. The highest predicted 24-h average concentrations sometimes exceeded 5000 µg m−3 in the first 500 m downwind of flaring and reached 71 µg m−3 within a kilometer of some in situ burns. Beyond 40 km from the DWH site, plumes appeared to be well mixed, and the predicted 24-h average concentrations from the flares and in situ burns were similar, usually below 10 µg m−3. Structured averaging of model output gave potential PM2.5 exposure estimates for OSRC workers located in various areas across the Gulf. Workers located nearest the wellhead (hot zone/source workers) were estimated to have a potential maximum 12-h exposure of 97 µg m−3 over the 2-month flaring period. The potential maximum 12-h exposure for workers who participated in in situ burns was estimated at 10 µg m−3 over the ~3-month burn period. The results suggest that burning of oil and gas during the DWH clean-up may have resulted in PM2.5 concentrations substantially above the U.S. National Ambient Air Quality Standard for PM2.5 (24-h average = 35 µg m−3). These results are being used to investigate possible adverse health effects in the GuLF STUDY epidemiologic analysis of PM2.5 exposures.

Background: Individuals affected by disasters are at risk for adverse mental health sequelae. Individuals living in the US Gulf Coast have experienced many recent major disasters, but few studies have explored the cumulative burden of experiencing multiple disasters on mental health. Objective: The objective of this study was to evaluate the relationship between disaster burden on mental health. Methods: We used data from 9,278 Gulf Long-term Follow-up Study participants who completed questionnaires on perceived stress, anxiety, depression, and post-traumatic stress disorder (PTSD) in 2011-2013. We linked 2005-2010 county-level data from the Spatial Hazard Events and Losses Database for the United States, a database of loss-causing events, to participant’s home address. Exposure measures included total count of loss events as well as severity quantified as property/crop losses per capita from all hazards. We used multilevel modeling to estimate odds ratios (OR) and 95% confidence intervals (CI) for each exposure-outcome relationship. Results: Total count of loss events was positively associated with perceived stress (ORQ4:1.40, 95% CI:1.21-1.61) and was inversely associated with PTSD (ORQ4:0.66, 95% CI 0.45-0.96). Total duration of exposure was also associated with stress (ORQ4:1.16, 95% CI 1.01-1.33) but not with other outcomes. Severity based on cumulative fatalities/injuries was associated with anxiety (ORQ4:1.31, 95% CI 1.05-1.63) and stress (ORQ4:1.34, 95% CI 1.15-1.57), and severity based on cumulative property/crop losses was associated with anxiety (ORQ4:1.42, 95% CI:1.12-1.81), depression (ORQ4:1.22, 95% CI:0.95-1.57) and PTSD (ORQ4:1.99, 95% CI:1.44-2.76). Significance: Higher natural hazard burden above and beyond individual disasters may increase risk for multiple adverse mental health outcomes.

Exposure to total hydrocarbons (THC) and volatile organic compounds from air pollution is associated with risk of coronary heart disease. THC exposure from oil spills might be similarly associated, but no research has examined this. We assessed the relationship between THC exposure during the response and cleanup of the Deepwater Horizon oil spill (Gulf of Mexico) and heart attack risk among 24,375 oil spill workers enrolled in the Gulf Long-Term Follow-up Study. There were 312 first heart attacks (self-reported physician-diagnosed myocardial infarction, or fatal coronary heart disease) ascertained during the study period (2010–2016). THC exposures were estimated using a job-exposure matrix incorporating self-reported activities and personal air measurements. We used Cox proportional hazards regression to estimate hazard ratios, with inverse-probability weights to account for confounding and censoring. Maximum THC levels of ≥0.30 parts per million (ppm) were associated with heart attack risk, with a 1.8-fold risk for exposure of ≥3.00 ppm versus

Large spatial datasets are typically modeled through a small set of knot locations; often these locations are specified by the investigator by arbitrary criteria. Existing methods of estimating the locations of knots assume their number is known a priori, or are otherwise computationally intensive. We develop a computationally efficient method of estimating both the location and number of knots for spatial mixed effects models. Our proposed algorithm, Threshold Knot Selection (TKS), estimates knot locations by identifying clusters of large residuals and placing a knot in the centroid of those clusters. We conduct a simulation study showing TKS in relation to several comparable methods of estimating knot locations. Our case study utilizes data of particulate matter concentrations collected during the course of the response and clean-up effort from the 2010 Deepwater Horizon oil spill in the Gulf of Mexico.

ImportanceExposure to hydrocarbons, fine particulate matter (PM2.5), and other chemicals from the April 20, 2010, Deepwater Horizon disaster may be associated with increased blood pressure and newly detected hypertension among oil spill response and cleanup workers.ObjectiveTo determine whether participation in cleanup activities following the disaster was associated with increased risk of developing hypertension.Design, Setting, and ParticipantsThis cohort study was conducted via telephone interviews and in-person home exams. Participants were 6846 adults who had worked on the oil spill cleanup (workers) and 1505 others who had completed required safety training but did not do cleanup work (nonworkers). Eligible participants did not have diagnosed hypertension at the time of the oil spill. Statistical analyses were performed from June 2018 to December 2021.ExposuresEngagement in cleanup activities following the Deepwater Horizon oil spill disaster, job classes, quintiles of cumulative total hydrocarbons exposure level, potential exposure to burning or flaring oil, and estimated PM2.5 were examined.Main Outcomes and MeasuresSystolic and diastolic blood pressure measurements were collected during home exams from 2011 to 2013 using automated oscillometric monitors. Newly detected hypertension was defined as antihypertensive medication use or elevated blood pressure since the spill. Log binomial regression was used to calculate prevalence ratios (PR) and 95% CIs for associations between cleanup exposures and hypertension. Multivariable linear regression was used to estimate exposure effects on continuous blood pressure levels.ResultsOf 8351 participants included in this study, 6484 (77.6%) were male, 517 (6.2%) were Hispanic, 2859 (34.2%) were non-Hispanic Black, and 4418 (52.9%) were non-Hispanic White; the mean (SD) age was 41.9 (12.5) years at enrollment. Among workers, the prevalence of newly detected hypertension was elevated in all quintiles (Q) of cumulative total hydrocarbons above the first quintile (PR for Q3, 1.29 [95% CI, 1.13-1.46], PR for Q4, 1.25 [95% CI, 1.10-1.43], and PR for Q5, 1.31 [95% CI, 1.15-1.50]). Both exposure to burning and/or flaring oil and gas (PR, 1.16 [95% CI, 1.02-1.33]) and PM2.5 from burning (PR, 1.26 [95% CI, 0.89-1.71]) for the highest exposure category were associated with increased risk of newly detected hypertension, as were several types of oil spill work including cleanup on water (PR, 1.34 [95% CI, 1.08-1.66]) and response work (PR, 1.51 [95% CI, 1.20-1.90]).Conclusions and RelevanceOil spill exposures were associated with newly detected hypertension after the Deepwater Horizon disaster. These findings suggest that blood pressure screening should be considered for workers with occupational hydrocarbon exposures.

BACKGROUND: Little is known about the effects of inhalation exposures on lung function among workers involved in the mitigation of oil spills. Our objective was to determine the relationship between oil spill response work and lung function 1–3 years after the Deepwater Horizon (DWH) disaster. METHODS: We evaluated spirometry for 7,775 adults living in the Gulf states who either participated in DWH response efforts (workers) or received safety training but were not hired (non-workers). At an enrollment interview, we collected detailed work histories including information on potential exposure to dispersants and burning oil/gas. We assessed forced expiratory volume in 1 second (FEV(1); mL), forced vital capacity (FVC; mL), and the ratio (FEV(1)/FVC%) for differences by broad job classes and exposure to dispersants or burning oil/gas using multivariable linear and modified Poisson regression. RESULTS: We found no differences between workers and non-workers. Among workers, we observed a small decrement in FEV(1) (Beta: −71 mL, 95% CI: −127, −14) in decontamination workers compared to support workers. Workers with high potential exposure to burning oil/gas had reduced lung function compared to unexposed workers: FEV(1) (Beta: −183 mL, 95% confidence interval[CI]: −316, −49) and FEV(1)/FVC (Beta: −1.93%, 95% CI: −3.50, −0.36), and an elevated risk of having a FEV(1)/FVC in the lowest tertile (prevalence ratio: 1.38, 95% CI: 0.99, 1.92). CONCLUSIONS: While no differences in lung function were found between workers and non-workers, lung function was reduced among decontamination workers and workers with high exposure to burning oil/gas compared to unexposed workers.

Both essential and non-essential metals come from natural and anthropogenic sources. Metals can bioaccumulate in humans and may impact human health, including hypertension.Blood metal (cadmium, lead, mercury, manganese, and selenium) concentrations were measured at baseline for a sample of participants in the Gulf Long-Term Follow-up (GuLF) Study. The GuLF Study is a prospective cohort study focused on potential health effects following the 2010 Deepwater Horizon oil spill. Hypertension was defined as high systolic (≥140 mm Hg) or diastolic (≥90 mm Hg) blood pressure or taking anti-hypertensive medications. A total of 957 participants who had blood measurement for at least one metal, baseline blood pressure measurements, information on any anti-hypertensive medication use, and relevant covariates were included in this cross-sectional analysis. We used Poisson regression to explore the association between individual blood metal levels and hypertension. Quantile-based g-computation was used to investigate the association between the metal mixture and hypertension. We also explored the association between individual blood metal levels and continuous blood pressure measurements using general linear regression.Comparing the highest quartile of blood metals with the lowest (Q4vs1), the hypertension prevalence ratio (PR) was 0.92 (95 % confidence interval (CI) = 0.73,1.15) for cadmium, 0.86 (95%CI = 0.66,1.12) for lead, 0.89 (95%CI = 0.71,1.12) for mercury, 1.00 (95%CI = 0.80,1.26) for selenium, and 1.22 (95%CI = 0.95,1.57) for manganese. We observed some qualitative differences across race and BMI strata although none of these differences were statistically significant. In stratified analyses, the PR (Q4vs1) for mercury was 0.69 (95%CI = 0.53, 0.91) in White participants and 1.29 (95%CI = 0.86,1.92) in Black participants (p for interaction = 0.5). The PR (Q4vs1) for manganese was relatively higher in Black participants (PR = 1.37, 95%CI = 0.92,2.05) than in White participants (PR = 1.15, 95%CI = 0.83,1.60, p for interaction = 0.5), with a suggestive dose-response among Blacks. After stratifying by obesity (BMI ≥30 and 30), positive associations of of hypertension with cadmium (PR [Q4vs1] = 1.19, 95%CI = 0.91,1.56, p for interaction = 0.5), lead (PR [Q4vs1] = 1.14, 95%CI = 0.84,1.55, p for interaction = 1.0) and manganese (PR = 1.25, 95%CI = 0.93,1.68, p for interaction = 0.8) were observed in participants with BMI≥30, but not in participants with BMI30. The joint effect of the metal mixture was 0.96 (95%CI = 0.73,1.27). We did not observe clear associations between blood metal levels and continuous blood pressure measurements.We did not find overall cross-sectional associations between blood cadmium, lead, mercury, selenium levels and hypertension or blood pressure. We found some evidence suggesting that manganese might be positively associated with risk of hypertension. Associations varied somewhat by race and BMI.

To address concerns among Gulf Coast residents about ongoing exposures to volatile organic compounds, including benzene, toluene, ethylbenzene, o-xylene, and m-xylene/p-xylene (BTEX), we characterized current blood levels and identified predictors of BTEX among Gulf state residents. We collected questionnaire data on recent exposures and measured blood BTEX levels in a convenience sample of 718 Gulf residents. Because BTEX is rapidly cleared from the body, blood levels represent recent exposures in the past 24 h. We compared participants' levels of blood BTEX to a nationally representative sample. Among nonsmokers we assessed predictors of blood BTEX levels using linear regression, and predicted the risk of elevated BTEX levels using modified Poisson regression. Blood BTEX levels in Gulf residents were similar to national levels. Among nonsmokers, sex and reporting recent smoky/chemical odors predicted blood BTEX. The change in log benzene was -0.26 (95% CI: -0.47, -0.04) and 0.72 (0.02, 1.42) for women and those who reported odors, respectively. Season, time spent away from home, and self-reported residential proximity to Superfund sites (within a half mile) were statistically associated with benzene only, however mean concentration was nearly an order of magnitude below that of cigarette smokers. Among these Gulf residents, smoking was the primary contributor to blood BTEX levels, but other factors were also relevant.

Background Studies of workers exposed to benzene at average air concentrations below one part per million suggest that benzene, a known hematotoxin, causes hematopoietic damage even at low exposure levels. However, evidence of such effects outside of occupational settings and for other volatile organic compounds (VOCs) is limited. Objective To investigate associations between ambient exposures to five VOCs, including benzene, and hematologic parameters among adult residents of the U.S. Gulf Coast. Materials and methods Blood concentrations of selected VOCs were measured in a sample of adult participants in the Gulf Long-term Follow-up Study (GuLF STUDY) during 2012 and 2013. Complete blood counts with differentials were also performed on a subset of participants (n=406). We used these data together with detailed questionnaire data to estimate adjusted associations between blood BTEXS (benzene, toluene, ethylbenzene, o-xylene, m/p-xylene, and styrene) concentrations and hematologic parameters using generalized linear models. Results We observed inverse associations between blood benzene concentrations and hemoglobin concentration and mean corpuscular hemoglobin concentration, and a positive association with red cell distribution width among tobacco smoke-unexposed participants (n=146). Among tobacco smoke-exposed participants (n=247), we observed positive associations between blood VOC concentrations and several hematologic parameters, including increased white blood cell and platelet counts, suggestive of hematopoietic stimulation typically associated with tobacco smoke exposure. Most associations were stronger for benzene than for the other VOCs. Conclusions Our results suggest that ambient exposure to BTEXS, particularly benzene, may be associated with hematologic effects, including decreased hemoglobin concentration, mean corpuscular hemoglobin concentration, and increased red cell distribution width.

Background: The 2010 Deepwater Horizon disaster led to the largest ever marine oil spill. Individuals who worked on the spill were exposed to toxicants and stressors that could lead to adverse effects. Objectives: The GuLF STUDY was designed to investigate relationships between oil spill exposures and multiple potential physical and mental health effects. Methods: Participants were recruited by telephone from lists of individuals who worked on the oil spill response and clean-up or received safety training. Enrollment interviews between 2011 and 2013 collected information about spill-related activities, demographics, lifestyle, and health. Exposure measurements taken during the oil spill were used with questionnaire responses to characterize oil exposures of participants. Participants from Gulf states completed a home visit in which biological and environmental samples, anthropometric and clinical measurements, and additional health and lifestyle information were collected. Participants are being followed for changes in health status. Results: Thirty-two thousand six hundred eight individuals enrolled in the cohort, and 11,193 completed a home visit. Most were young (56.2% ≤ 45 years of age), male (80.8%), lived in a Gulf state (82.3%), and worked at least 1 day on the oil spill (76.5%). Workers were involved in response (18.0%), support operations (17.5%), clean-up on water (17.4%) or land (14.6%), decontamination (14.3%), and administrative support (18.3%). Using an ordinal job exposure matrix, 45% had maximum daily total hydrocarbon exposure levels ≥ 1.0 ppm. Conclusions: The GuLF STUDY provides a unique opportunity to study potential adverse health effects from the Deepwater Horizon oil spill. Citation: Kwok RK, Engel LS, Miller AK, Blair A, Curry MD, Jackson WB II, Stewart PA, Stenzel MR, Birnbaum LS, Sandler DP for the GuLF STUDY Research Team. 2017. The GuLF STUDY: a prospective study of persons involved in the Deepwater Horizon oil spill response and clean-up. Environ Health Perspect 125:570–578; http://dx.doi.org/10.1289/EHP715

Oil spill response and clean-up (OSRC) workers were exposed to hazardous airborne chemicals following the 2010 Deepwater Horizon disaster. The aim of this study was to evaluate lung function in workers 4–6 years following the disaster using a prospective cohort. Participants who completed two spirometry test sessions 1–3 years, and 4–6 years after the spill (N = 1,838) were included and forced expiratory volume in 1 s (FEV1; ml), forced vital capacity (FVC; ml), and ratio (FEV1/FVC; %) determined. Linear mixed models were utilized to estimate relationships between OSRC exposures and lung function 4–6 years after the spill and changes since the prior measurement. Despite suggestive reduced lung function at 1–3 years, at the 4–6-year exam workers with total hydrocarbon (THC) exposure 1–2.99 ppm and ≥3 ppm compared to those with ≤0.29 ppm exhibited higher FEV1 (β: 108 ml, 95% CI: 17, 198) and (β: 118 ml, 95% CI: 5, 232), respectively. Compared with support workers, those in higher exposed jobs displayed greater improvement in FEV1 between visits: cleanup on water (β: 143 ml, 95% CI: 35, 250), operations (β: 132 ml, 95% CI: 30, 234) and response (β: 149 ml, 95% CI: 43, 256). Greater FEV1 improvement was also associated with higher versus the lowest level THC exposure: 1–2.99 ppm (β: 134 ml, 95% CI: 57, 210) and ≥3 ppm (β: 205 ml, 95% CI: 109, 301). Lung function decrements seen shortly after the spill were no longer apparent 4–6 years later, with the greatest improvement among those with the highest exposures.

Increasing in frequency and impact in the United States and worldwide, disasters can lead to serious mental health consequences. Although US census data are essential for disaster preparedness and the identification of community-level risk factors for adverse postdisaster mental health outcomes, the US Census Bureau faces many challenges as we approach 2020 Decennial Census data collection. Despite the utility of the information provided by the Census and American Community Survey (ACS), the 2020 US Census and subsequent ACS data face threats to validity. As a result, public health funding could be misallocated, and disaster preparedness and response efforts misinformed; this can also contribute to the worsening of mental health inequities, particularly in the context of disaster. Undercutting the Census and the ACS, rich data sources that allow representation of all people in the United States, is a step backward in our effort to mitigate the population mental health consequences of disasters.

Although styrene is an established neurotoxicant at occupational exposure levels, its neurotoxicity has not been characterized in relation to general population exposures. Further, occupational research to date has focused on central nervous system impairment.We assessed styrene-associated differences in sensory and motor function among Gulf coast residents.We used 2011 National Air Toxics Assessment estimates of ambient styrene to determine exposure levels for 2,956 nondiabetic Gulf state residents enrolled in the Gulf Long-term Follow-up Study, and additionally measured blood styrene concentration in a subset of participants 1 to 2 y after enrollment ([Formula: see text]). Participants completed an enrollment telephone interview and a comprehensive test battery to assess sensory and motor function during a clinical follow-up exam 2 to 4 y later. Detailed covariate information was ascertained at enrollment via telephone interview. We used multivariate linear regression to estimate continuous differences in sensory and motor function, and log-binomial regression to estimate prevalence ratios for dichotomous outcomes. We estimated associations of both ambient and blood styrene exposures with sensory and motor function, independently for five unique tests.Those participants in the highest 25% vs. lowest 75% of ambient exposure and those in the highest 10% vs. lowest 90% of blood styrene had slightly diminished visual contrast sensitivity. Mean vibrotactile thresholds were lower among those in the highest vs. lowest quartile of ambient styrene and the highest 10% vs. lowest 90% of blood styrene ([Formula: see text] log microns; 95% CI: [Formula: see text], [Formula: see text] and [Formula: see text] log microns; 95% CI: [Formula: see text], [Formula: see text], respectively). The highest vs. lowest quartile of ambient styrene was associated with significantly poorer postural stability, and (unexpectedly) with significantly greater grip strength.We observed associations between higher styrene exposure and poorer visual, sensory, and vestibular function, though we did not detect associations with reduced voluntary motor system performance. Associations were more consistent for ambient exposures, but we also found notable associations with measured blood styrene. https://doi.org/10.1289/EHP3954.

Background The chemicals benzene, toluene, ethylbenzene, and xylenes (BTEX) are neuroactive. Exposures often co-occur because they share common sources. We examined neurologic effects of environmental BTEX exposure among U.S. Gulf coast residents taking into account concomitant exposures. Methods We measured blood concentrations of BTEX in 690 Gulf state residents. Neurologic symptoms were ascertained via telephone interview. We used log-binomial regression to estimate associations between blood BTEX levels and self-reported neurologic symptoms independently for the presence of any neurologic, central (CNS), or peripheral nervous system (PNS) symptoms. We estimated associations in single chemical models mutually adjusted for co-occurring BTEX and used weighted quantile sum regression to model associations between the combined BTEX mixture and neurologic symptoms. Results Half (49%) of participants reported at least one neurologic symptom. Each BTEX chemical was associated with increased CNS and PNS symptoms in single-chemical models comparing the highest to lowest quartile of exposure. After adjusting for coexposures, benzene was associated with CNS symptoms among all participants (PR = 2.13, 95% CI: 1.27, 3.57) and among nonsmokers (PR = 2.30, 95% CI: 1.35, 3.91). After adjusting for coexposures, associations with toluene were apparent only for reporting multiple PNS symptoms (PR = 2.00, 95% CI: 0.96, 4.16). In mixture analyses, a one-quartile increase in BTEX exposure was associated with neurologic symptoms (OR = 1.47, 95% CI: 1.11, 1.98). The weighted quantile sum index weighted benzene most heavily, which was consistent with single chemical analyses. Conclusions Increasing blood benzene concentration was associated with increased prevalence of CNS symptoms. In this sample, BTEX-associated neurologic effects are likely driven by exposure to benzene and, to a lesser extent, toluene.

Natural and anthropogenic disaster-related experiences can exacerbate background stressors, which may lead to negative mental health outcomes [1]. However, few studies have assessed mental health indicators related to measured lung function in the aftermath of a disaster. In 2010 the Deepwater Horizon ( DWH ) disaster resulted in the largest maritime oil spill in US history and negatively affected proximal communities, which experienced increased distress and post-traumatic stress disorder (PTSD)-like symptoms attributed to the disaster [2, 3]. We investigated the relationship between mental health indicators and lung function following this disaster. Footnotes This manuscript has recently been accepted for publication in the European Respiratory Journal . It is published here in its accepted form prior to copyediting and typesetting by our production team. After these production processes are complete and the authors have approved the resulting proofs, the article will move to the latest issue of the ERJ online. Please open or download the PDF to view this article. Conflict of interest: Dr. Lawrence has nothing to disclose. Conflict of interest: Dr. Werder has nothing to disclose. Conflict of interest: Dr. Kwok has nothing to disclose. Conflict of interest: Dr. Engel has nothing to disclose. Conflict of interest: Dr. Sandler has nothing to disclose.

In April 2010, the Deepwater Horizon oil rig caught fire and exploded, releasing almost 5 million barrels of oil into the Gulf of Mexico over the ensuing 3 months. Thousands of oil spill workers participated in the spill response and clean-up efforts. The GuLF STUDY being conducted by the National Institute of Environmental Health Sciences is an epidemiological study to investigate potential adverse health effects among these oil spill clean-up workers. Many volatile chemicals were released from the oil into the air, including total hydrocarbons (THC), which is a composite of the volatile components of oil including benzene, toluene, ethylbenzene, xylene, and hexane (BTEXH). Our goal is to estimate exposure levels to these toxic chemicals for groups of oil spill workers in the study (hereafter called exposure groups, EGs) with likely comparable exposure distributions. A large number of air measurements were collected, but many EGs are characterized by datasets with a large percentage of censored measurements (below the analytic methods' limits of detection) and/or a limited number of measurements. We use THC for which there was less censoring to develop predictive linear models for specific BTEXH air exposures with higher degrees of censoring. We present a novel Bayesian hierarchical linear model that allows us to predict, for different EGs simultaneously, exposure levels of a second chemical while accounting for censoring in both THC and the chemical of interest. We illustrate the methodology by estimating exposure levels for several EGs on the Development Driller III, a rig vessel charged with drilling one of the relief wells. The model provided credible estimates in this example for geometric means, arithmetic means, variances, correlations, and regression coefficients for each group. This approach should be considered when estimating exposures in situations when multiple chemicals are correlated and have varying degrees of censoring.