Estimates of Occupational Inhalation Exposures to Six Oil-Related Compounds on the Four Rig Vessels Responding to the Deepwater Horizon Oil Spill.

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.

Linear Relationships Between Total Hydrocarbons and Benzene, Toluene, Ethylbenzene, Xylene, and n-Hexane during the Deepwater Horizon Response and Clean-up.

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.

Life expectancy and mortality in 363 cities of Latin America.

The concept of a so-called urban advantage in health ignores the possibility of heterogeneity in health outcomes across cities. Using a harmonized dataset from the SALURBAL project, we describe variability and predictors of life expectancy and proportionate mortality in 363 cities across nine Latin American countries. Life expectancy differed substantially across cities within the same country. Cause-specific mortality also varied across cities, with some causes of death (unintentional and violent injuries and deaths) showing large variation within countries, whereas other causes of death (communicable, maternal, neonatal and nutritional, cancer, cardiovascular disease and other noncommunicable diseases) varied substantially between countries. In multivariable mixed models, higher levels of education, water access and sanitation and less overcrowding were associated with longer life expectancy, a relatively lower proportion of communicable, maternal, neonatal and nutritional deaths and a higher proportion of deaths from cancer, cardiovascular disease and other noncommunicable diseases. These results highlight considerable heterogeneity in life expectancy and causes of death across cities of Latin America, revealing modifiable factors that could be amenable to urban policies aimed toward improving urban health in Latin America and more generally in other urban environments.

Exploration of the use of Bayesian modeling of gradients for censored spatiotemporal data from the Deepwater Horizon oil spill.

This paper develops a hierarchical framework for identifying spatiotemporal patterns in data with a high degree of censoring using the gradient process. To do this, we impute censored values using a sampling-based inverse CDF method within our Markov chain Monte Carlo algorithm, thereby avoiding burdensome integration and facilitating efficient estimation of other model parameters. We illustrate use of our methodology using a simulated data example, and uncover the danger of simply substituting a space- and time-constant function of the level of detection for all missing values. We then fit our model to area measurement data of volatile organic compounds (VOC) air concentrations collected on vessels supporting the response and clean-up efforts of the Deepwater Horizon oil release that occurred starting April 20, 2010. These data contained a high percentage of observations below the detectable limits of the measuring instrument. Despite this, we were still able to make some interesting discoveries, including elevated levels of VOC near the site of the oil well on June 26th. Using the results from this preliminary analysis, we hope to inform future research on the Deepwater Horizon study, including the use of gradient methods for assigning workers to exposure categories.

High-density lipoprotein particles and markers of inflammation and thrombotic activity in patients with untreated HIV infection.

BACKGROUND: Untreated human immunodeficiency virus (HIV) infection is associated with changes in blood lipids, inflammation, thrombotic activity, and increased risk for cardiovascular disease. METHODS: We studied high-density lipoprotein particle (HDLp) concentrations and inflammatory (high-sensitivity C-reactive protein [hsCRP] and interleukin [IL] 6), endothelial activation (E-selectin and soluble intercellular adhesion molecule-1 [sICAM-1]), and thrombotic (fibrinogen and D-dimer) biomarkers in a group of 32 untreated HIV-infected and 29 uninfected persons. Differences in the levels of blood lipids and biomarkers by HIV status were examined before and after adjustment for age, sex, race/ethnicity, smoking status, body mass index, and the presence of hepatitis C. RESULTS: HIV-infected participants, compared with uninfected participants, had lower HDL cholesterol (HDLc) levels (-26%) and HDLp numbers (-21%), with reductions in large (-50%) and small (-20%) HDLp, specifically (P < or = .01 for all). A trend was present for higher total cholesterol (P = .15 and triglyceride levels (P = .11) among individuals with HIV infection. Levels of IL-6, sICAM-1, and D-dimer were 65%-70% higher in HIV-infected participants (P < or = .02 for all). Covariate adjustment did not diminish these associations. For HIV-infected participants, total and small HDLp (respectively) tended to correlate inversely with levels of IL-6 (P = .08 and P = .02), sICAM-1 (P < .01 for both) and D-dimer (P = .03 and p < .01). CONCLUSIONS: Persons with untreated HIV infection have lower HDLp (primarily large and small HDLp) and higher IL-6, sICAM-1, and D-dimer levels, and the relationship of these markers to HIV-mediated atherosclerotic risk requires further study.

Untreated HIV infection and large and small artery elasticity.

BACKGROUND: Untreated HIV infection may increase risk for cardiovascular disease, and arterial elasticity is a marker of cardiovascular risk and early disease. METHODS: HIV-infected participants not taking antiretroviral therapy (n=32) were compared with HIV-negative controls (n=30). Large and small artery elasticity (LAE and SAE) were estimated via analysis of radial pulse waveforms. Differences in LAE and SAE by HIV status were compared using analysis of covariance, with and without adjustment for Framingham risk (model 1); covariates that differed between groups [smoking, injection drug use, hepatitis C, and high-density lipoprotein cholesterol (HDLc); model 2]; or age, sex, race/ethnicity, smoking, injection frug use, hepatitis C, HDLc, and non-HDLc (model 3). RESULTS: HIV infection was associated with impaired LAE (-2.55 mL/mm Hg x 10; P=0.02) and SAE (-1.50 mL/mm Hg x 100; P=0.02). Associations with traditional risk factors were often stronger for SAE than LAE, including with Framingham score (per 1% higher; SAE -0.18, P=0.01; LAE -0.19, P=0.13). Fasting lipid levels were not significantly associated with LAE and SAE. After adjustment, differences between HIV-infected and HIV-uninfected participants were similar in model 1 (-2.36 for LAE, P=0.04; -1.31 for SAE, P=0.04), model 2 (-2.67 for LAE, P=0.02; -1.13 for SAE, P=0.07) and model 3 (-2.91 for LAE, P=0.02; -1.34 for SAE, P=0.03). CD4 count and HIV RNA level were not associated with LAE and SAE among HIV-infected participants. CONCLUSIONS: Untreated HIV infection is associated with impaired arterial elasticity, of both the large and small vasculature, after controlling for additional risk factors. Pulse waveform analysis is a noninvasive technique to assess cardiovascular disease risk that should be evaluated in larger studies of HIV-infected persons.