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Quantifying the exposome is key to understanding how the environment impacts human health and disease. However, accurately, and cost-effectively quantifying exposure in large population health studies remains a major challenge. Geospatial technologies offer one mechanism to integrate high-dimensional environmental data into epidemiology studies, but can present several challenges. In June 2021, the National Institute of Environmental Health Sciences (NIEHS) held a workshop bringing together experts in exposure science, geospatial technologies, data science and population health to address the need for integrating multiscale geospatial environmental data into large population health studies. The primary objectives of the workshop were to highlight recent applications of geospatial technologies to examine the relationships between environmental exposures and health outcomes; identify research gaps and discuss future directions for exposure modeling, data integration and data analysis strategies; and facilitate communications and collaborations across geospatial and population health experts. This commentary provides a high-level overview of the scientific topics covered by the workshop and themes that emerged as areas for future work, including reducing measurement errors and uncertainty in exposure estimates, and improving data accessibility, data interoperability, and computational approaches for more effective multiscale and multi-source data integration, along with potential solutions.

Introduction: Oil spill response and cleanup (OSRC) workers had potentially stressful experiences during mitigation efforts following the 2010 Deepwater Horizon disaster. Smelling chemicals; skin or clothing contact with oil; heat stress; handling oily plants/wildlife or dead animal recovery; and/or being out of regular work may have posed a risk to worker respiratory health through psychological stress mechanisms. Objective: To evaluate the association between six potentially stressful oil spill experiences and lung function among OSRC workers 1–3 years following the Deepwater Horizon disaster, while controlling for primary oil spill inhalation hazards and other potential confounders. Methods: Of 6811 GuLF STUDY participants who performed OSRC work and completed a quality spirometry test, 4806 provided information on all exposures and confounders. We carried out complete case analysis and used multiple imputation to assess risk among the larger sample. Potentially stressful work experiences were identified from an earlier study of these workers. The lung function parameters of interest include the forced expiratory volume in 1 s (FEV1, mL), the forced vital capacity (FVC, mL) and the ratio (FEV1/FVC, %). Results: On average, participants in the analytic sample completed spirometry tests 1.7 years after the spill. Among workers with at least 2 acceptable FEV1 and FVC curves, workers with jobs that involved oily plants/wildlife or dead animal recovery had lower values for FEV1 (Mean difference: −53 mL, 95% CI: −84, −22), FVC (Mean difference: −45 mL, 95% CI: −81, −9) and FEV1/FVC (Mean difference: −0.44%, 95% CI: −0.80, −0.07) compared to unexposed workers in analyses using multiple imputation. Conclusions: Workers involved in handling oily plants/wildlife or dead animal recovery had lower lung function than unexposed workers after accounting for other OSRC inhalation hazards. Keywords: Lung function, Spirometry, Nonchemical stressors, Oil spill, Deepwater Horizon

Background: Styrene is an established neurotoxicant at occupational levels, but effects at levels relevant to the general population have not been studied. We examined the neurologic effects of environmental styrene exposure among U.S. Gulf coast residents. Methods: We used National Air Toxics Assessment (NATA) 2011 estimates of ambient styrene concentrations to assign exposure levels for 21,962 non-diabetic Gulf state residents, and additionally measured blood styrene concentration in a subset of participants (n = 874). Neurologic symptoms, as well as detailed covariate information, were ascertained via telephone interview. We used log-binomial regression to estimate prevalence ratios (PR) and 95% confidence intervals (95% CI) for cross-sectional associations between both ambient and blood styrene levels and self-reported neurologic symptoms. We estimated associations independently for ten unique symptoms, as well as for the presence of any neurologic, central nervous system (CNS), or peripheral nervous system (PNS) symptoms. We also examined heterogeneity of associations with estimated ambient styrene levels by race and sex. Results: One-third of participants reported at least one neurologic symptom. The highest quartile of estimated ambient styrene was associated with one or more neurologic (PR, 1.12; 95% CI: 1.07,1.18), CNS (PR, 1.17; 95% CI: 1.11,1.25), and PNS (PR, 1.16; 95% CI: 1.09,1.25) symptom. Results were less consistent for biomarker analyses, but blood styrene level was suggestively associated with nausea (PR, 1.78; 95% CI: 1.04, 3.03). In stratified analyses, we observed the strongest effects among non-White participants. Conclusions: Increasing estimated ambient styrene concentration was consistently associated with increased prevalence of neurologic symptoms. Associations between blood styrene levels and some neurologic symptoms were suggestive. Environmental styrene exposure levels may be sufficient to elicit symptomatic neurotoxic effects. Keywords: Air pollution, Nervous system, Styrene, Biomarker, Neurologic

Abstract Background Workers involved in the response and clean-up of the 2010 Deepwater Horizon oil spill faced possible exposures to crude oil, burning oil, dispersants and other pollutants in addition to physical and emotional stress. These exposures may have increased risk of myocardial infarction (MI) among oil spill workers. Methods Gulf Long-term Follow-up (GuLF) STUDY participants comprise individuals who either participated in the Deepwater Horizon response efforts or registered for safety training but were not hired. Oil spill-related exposures were assessed during enrollment interviews conducted in 2011–2013. We estimated risk ratios (RR) and 95% confidence intervals for the associations of clean-up work characteristics with self-reported nonfatal MI up to three years post-spill. Results Among 31,109 participants without history of MI prior to the spill, 77% worked on the oil spill. There were 192 self-reported MI during the study period; 151 among workers. Among the full cohort, working on the oil spill clean-up (vs not working on the clean-up) and living in proximity to the oil spill (vs further away) were suggestively associated with a possible increased risk of nonfatal MI [RR: 1.22 (0.86, 1.73) and 1.15 (0.82, 1.60), respectively]. Among oil spill workers, working for > 180 days was associated with MI [RR for > 180 days (vs 1–30 days): 2.05 (1.05, 4.01)], as was stopping working due to heat [RR: 1.99 (1.43, 2.78)]. There were suggestive associations of maximum total hydrocarbon exposure ≥3.00 ppm (vs 180 days and stopping work due to heat increased risk of nonfatal MI. Future research should evaluate whether the observed associations are related to specific chemical exposures or other stressors associated with the spill.

Abstract Few conceptual frameworks attempt to connect disaster‐associated environmental injuries to impacts on ecosystem services (the benefits humans derive from nature) and thence to both psychological and physiological human health effects. To our knowledge, this study is one of the first, if not the first, to develop a detailed conceptual model of how degraded ecosystem services affect cumulative stress impacts on the health of individual humans and communities. Our comprehensive Disaster‐Pressure State‐Ecosystem Services‐Response‐Health model demonstrates that oil spills, hurricanes, and other disasters can change key ecosystem components resulting in reductions in individual and multiple ecosystem services that support people's livelihoods, health, and way of life. Further, the model elucidates how damage to ecosystem services produces acute, chronic, and cumulative stress in humans which increases risk of adverse psychological and physiological health outcomes. While developed and initially applied within the context of the Gulf of Mexico, it should work equally well in other geographies and for many disasters that cause impairment of ecosystem services. Use of this new tool will improve planning for responses to future disasters and help society more fully account for the costs and benefits of potential management responses. The model also can be used to help direct investments in improving response capabilities of the public health community, biomedical researchers, and environmental scientists. Finally, the model illustrates why the broad range of potential human health effects of disasters should receive equal attention to that accorded environmental damages in assessing restoration and recovery costs and time frames.

Summary: Background: Adverse mental health effects have been reported following oil spills but few studies have identified specific responsible attributes of the clean-up experience. We aimed to analyse the effects of the 2010 Deepwater Horizon (Gulf of Mexico) disaster on the mental health of individuals involved in oil spill response and clean-up. Methods: We used data from the Gulf Long-term Follow-up Study, a cohort of workers and volunteers involved in oil spill clean-up after the Deepwater Horizon disaster. We included 8968 workers (hired after completing training for oil spill response and clean-up) and 2225 non-workers (completed training but were not hired) who completed a Patient Health Questionnaire-8 and four-item Primary Care PTSD Screen to assess for probable depression and post-traumatic stress disorder (PTSD) indicators. Participants were recruited between March 28, 2011, and March 29, 2013. The mental health indicators were assessed at home visits done between May 12, 2011, and May 15, 2013. We used regression models to analyse the effect of potentially stressful job experiences, job type, and total hydrocarbon exposure on mental health indicators. Findings: Oil spill response and clean-up work was associated with increased prevalence of depression (prevalence ratio [PR] 1·22, 95% CI 1·08â1·37) and PTSD (PR 1·35, 95% CI 1·07â1·71). Among workers, individuals who reported smelling oil, dispersants, or cleaning chemicals had an elevated prevalence of depression (1·56, 1·37â1·78) and PTSD (2·25, 1·71â2·96). Stopping work because of the heat was also associated with depression (1·37, 1·23â1·53) and PTSD (1·41, 1·15â1·74), as was working as a commercial fisherman before the spill (1·38, 1·21â1·57; and 2·01, 1·58â2·55, respectively). An increase in exposure to total hydrocarbons appeared to be associated with depression and PTSD, but after taking into account oil spill job experiences, only the association between the highest amount of total hydrocarbons and PTSD remained (1·75, 1·11â2·76). Interpretation: Oil spill clean-up workers with high amounts of total hydrocarbon exposure or potentially stressful job experiences had an increased prevalence of depression and PTSD. These findings provide evidence that response and clean-up work is associated with adverse psychological effects and suggest the need for mental health services both before and after the event. Funding: National Institutes of Health (NIH) Common Fund and the Intramural Research Program of the NIH, National Institute of Environmental Health Sciences.

Individual exposure to ultraviolet radiation (UVR) is challenging to measure, particularly for diseases with substantial latency periods between first exposure and diagnosis of outcome, such as cancer. To guide the choice of surrogates for long-term UVR exposure in epidemiologic studies, we assessed how well stable sun-related individual characteristics and environmental/meteorological factors predicted daily personal UVR exposure measurements.We evaluated 123 United States Radiologic Technologists subjects who wore personal UVR dosimeters for 8 hours daily for up to 7 days (N = 837 days). Potential predictors of personal UVR derived from a self-administered questionnaire, and public databases that provided daily estimates of ambient UVR and weather conditions. Factors potentially related to personal UVR exposure were tested individually and in a model including all significant variables.The strongest predictors of daily personal UVR exposure in the full model were ambient UVR, latitude, daily rainfall, and skin reaction to prolonged sunlight (R(2) = 0.30). In a model containing only environmental and meteorological variables, ambient UVR, latitude, and daily rainfall were the strongest predictors of daily personal UVR exposure (R(2) = 0.25).In the absence of feasible measures of individual longitudinal sun exposure history, stable personal characteristics, ambient UVR, and weather parameters may help estimate long-term personal UVR exposure.