Exposure Science Research Articles

Exposure Health Informatics Methods for Environment Epidemiological Research

Traditional environmental epidemiology has relied on assessing individual exposures and their effects. Exposure science methods provides opportunities to advance epidemiological studies considering multiple and consequent exposures and over extended periods of time. Materializing the exposome concept requires methods to collect, integrate and assimilate data from multiple exposures including at personal levels, genomics, personal activities, locations, socio-behaviors, biomarkers of exposures, physiological effects, and health outcomes - all with appropriate spatiotemporal descriptions and associated uncertainties in measurements. Such an exposome requires integration of data from wearable and stationary sensors, environmental monitors, physiology, medication use and other clinical data. In addition, such an integration needs to have a high spatial-temporal resolution for correlating times and location of exposures to occurrences of conditions and their severities. This would require filling any gaps in the measured data with modeled data along with characterization of any uncertainties. Informatics is the scientific field that deals with biomedical information, data, and knowledge - their storage, retrieval, and optimal use for problem solving and decision-making. Recently, informatics methods are being developed, evaluated and utilized in sphere of environmental epidemiological and the exposome. In this symposium, we define the novel informatics sub-field, Exposure Health Informatics, and discuss challenges that require development of informatics methods. We then formally describe informatics methods that address these challenges, and their implementation as a scalable computation infrastructure, the Exposure Health Informatics Ecosystem (EHIE). EHIE is a comprehensive, standards-based, open-source informatics platform that provides semantically consistent, metadata-driven, event-based management of exposomic data consisting of sensor data acquisition pipelines, participant and researcher facing tools, computational modeling, and big data integration platform. Finally, with PRISMS pediatric asthma, Environmental Children’s Health Outcomes, diabetes and molecular epidemiological studies as exemplars, we discuss the generalizability of these multi-scale and multi-omics informatics methods for providing epidemiological researchers with robust reproducible pipelines.

Exposure science in an infectious disease pandemic: who do we want to be?

Exposure science in an infectious disease pandemic: who do we want to be?

Recent Advances in Occupational Exposure Assessment of Aerosols.

Exposure science is underpinned by characterization (measurement) of exposures. In this article, six recent advances in exposure characterization by sampling and analysis are reviewed as tools in the occupational exposure assessment of aerosols. Three advances discussed in detail are (1) recognition and inclusion of sampler wall deposits; (2) development of a new sampling and analytical procedure for respirable crystalline silica that allows non-destructive field analysis at the end of the sampling period; and (3) development of a new sampler to collect the portion of sub-300 nm aerodynamic diameter particles that would deposit in human airways. Three additional developments are described briefly: (4) a size-selective aerosol sampler that allows the collection of multiple physiologically-relevant size fractions; (5) a miniaturized pump and versatile sampling head to meet multiple size-selective sampling criteria; and (6) a novel method of sampling bioaerosols including viruses while maintaining viability. These recent developments are placed in the context of the historical evolution in sampling and analytical developments from 1900 to the present day. While these are not the only advances in exposure characterization, or exposure assessment techniques, they provide an illustration of how technological advances are adding more tools to our toolkit. The review concludes with a number of recommended areas for future research, including expansion of real-time and end-of-shift on-site measurement, development of samplers that operate at higher flow-rates to ensure measurement at lowered limit values, and development of procedures that accurately distinguish aerosol and vapor phases of semi-volatile substances.

Exposure Science in the 21st Century: Advancing the Science and Technology of Environmental Sensors through Cooperation and Collaboration across U.S. Federal Agencies.

The convergence of technological innovations in areas such as microelectronics, fabrication, the Internet-of-things (IoT), and smartphones, along with their associated “apps”, permeates many aspects of life. To that list we now can add environmental monitoring. Once the sole purview of governments and academics in research, this sector is currently experiencing a transformation that is democratizing monitoring with inexpensive, portable commodities available through online retailers. However, as with any emerging area, several challenges and infrastructural hurdles must be addressed before this technology can be fully adopted and its potential be realized. A unique aspect of environmental sensing that differentiates it from some other technology sectors is its strong intersection and overlap with governance, public policy, public health, and national security—all of which contain some element of inherent governmental function. This paper advocates for and addresses the role of sensors in exposure science and illustrates areas in which improved coordination and leveraging of investments by government have helped and would catalyze further development of this technology sector.

Development of a Web-Based Tool for Risk Assessment and Exposure Control Planning of Silica-Producing Tasks in the Construction Sector.

We describe the development and implementation of a novel, on-line risk assessment tool for respirable crystalline silica (RCS) exposure for use in the construction sector. It was motivated by the introduction of new OHS regulation in British Columbia that allowed for the substitution of exposure measurement data with “objective air monitoring data” collected at “equivalent work operations.” This allowance encouraged the introduction of quantitative risk assessment in a notoriously challenging work environment but it was concluded that without assistance, the typical construction employer would struggle to identify, extract, and interpret validate objective data. The tool described here was based on a continually-updatable RCS exposure database, and a predictive regression model based on the database to generate exposure risk estimates. The model was embedded in an adaptive web-based application that can be run on common platforms. The design followed standard web conventions and features so that no specialized training is required for its use. It was designed to be usable by end-users with varying expertise, including non-OHS experts. Users describe the RCS-dust generating task they will perform, and associated control measures. The tool estimates both uncontrolled and controlled task-based exposure concentrations. Using additional information entered by the user, the on-line tool generates an “exposure control plan” or ECP, a legally regulated document for those undertaking work potentially exposing workers to RCS particulate. The development of the tool was a community-based, tri-partite effort of the local OHS regulator, construction employers, and exposure scientists. In addition to being a practical risk assessment tool, the designers wanted it to function as an educational tool, and that it should explore novel methods for exposure data collection and use. The strengths of this approach include the publicly shared updateable database that encourages continuous improvement and illustrates best practices; and the timely and cost effective collection and sharing of exposure data in a value-added manner. It is however limited to a single task per ECP, and only considers exposure to task operators, and not adjacent workers. Currently in BC, users generate up to 3,900 ECP's per year with the tool.

Advancing methodologies for applying machine learning and evaluating spatiotemporal models of fine particulate matter (PM2.5) using satellite data over large regions.

Reconstructing the distribution of fine particulate matter (PM2.5) in space and time, even far from ground monitoring sites, is an important exposure science contribution to epidemiologic analyses of PM2.5 health impacts. Flexible statistical methods for prediction have demonstrated the integration of satellite observations with other predictors, yet these algorithms are susceptible to overfitting the spatiotemporal structure of the training datasets. We present a new approach for predicting PM2.5 using machine-learning methods and evaluating prediction models for the goal of making predictions where they were not previously available. We apply extreme gradient boosting (XGBoost) modeling to predict daily PM2.5 on a 1×1 km2 resolution for a 13 state region in the Northeastern USA for the years 2000-2015 using satellite-derived aerosol optical depth and implement a recursive feature selection to develop a parsimonious model. We demonstrate excellent predictions of withheld observations but also contrast an RMSE of 3.11 μg/m3 in our spatial cross-validation withholding nearby sites versus an overfit RMSE of 2.10 μg/m3 using a more conventional random ten-fold splitting of the dataset. As the field of exposure science moves forward with the use of advanced machine-learning approaches for spatiotemporal modeling of air pollutants, our results show the importance of addressing data leakage in training, overfitting to spatiotemporal structure, and the impact of the predominance of ground monitoring sites in dense urban sub-networks on model evaluation. The strengths of our resultant modeling approach for exposure in epidemiologic studies of PM2.5 include improved efficiency, parsimony, and interpretability with robust validation while still accommodating complex spatiotemporal relationships.

In Memoriam: Kirk R. Smith.

In Memoriam: Kirk R. Smith.

Translational data analytics in exposure science and environmental health: a citizen science approach with high school students

BackgroundTranslational data analytics aims to apply data analytics principles and techniques to bring about broader societal or human impact. Translational data analytics for environmental health is an emerging discipline and the objective of this study is to describe a real-world example of this emerging discipline.MethodsWe implemented a citizen-science project at a local high school. Multiple cohorts of citizen scientists, who were students, fabricated and deployed low-cost air quality sensors. A cloud-computing solution provided real-time air quality data for risk screening purposes, data analytics and curricular activities.ResultsThe citizen-science project engaged with 14 high school students over a four-year period that is continuing to this day. The project led to the development of a website that displayed sensor-based measurements in local neighborhoods and a GitHub-like repository for open source code and instructions. Preliminary results showed a reasonable comparison between sensor-based and EPA land-based federal reference monitor data for CO and NOx.ConclusionsInitial sensor-based data collection efforts showed reasonable agreement with land-based federal reference monitors but more work needs to be done to validate these results. Lessons learned were: 1) the need for sustained funding because citizen science-based project timelines are a function of community needs/capacity and building interdisciplinary rapport in academic settings and 2) the need for a dedicated staff to manage academic-community relationships.

Perspectives on advancing consumer product exposure models.

Predictive models are used to estimate exposures from consumer products to support risk management decision-making. These model predictions may be used alone in the absence of measured data or integrated with available exposure data. When different models are used, the resulting estimates of exposure and conclusions of risk may be disparate and the origin of these differences may not be obvious. This Perspectives Paper provides recommendations that could promote more systematic evaluation and a wider range of applicability of consumer product exposure models and their predictions, improve confidence in model predictions, and result in more accurate communication of consumer exposure model estimates. Key insights for the exposure science community to consider include: consistency in product descriptions, exposure routes, and scenarios; consistent and explicit definitions of exposure metrics; situation-dependent benefits from using one or multiple models; distinguishing between model algorithms and exposure factors; and corroboration of model predictions with measured data.

Estimating Children's Soil and Dust Ingestion Rates for Exposure Science (EPA)

Estimating Children's Soil and Dust Ingestion Rates for Exposure Science (EPA)

4549 Reproducible Informatics for Reproducible Translational Research

4549 Reproducible Informatics for Reproducible Translational Research

The relationship between personal exposure and ambient PM2.5 and black carbon in Beijing

This study is part of the “Air Polluion Impacts on Cardiopulmonary disease in Beijing: an integrated study of Exposure Science, Toxicologenomics & Environmental Epidemiology (APIC-ESTEE)” project under the UK-China joint research programme “Atmospheric Pollution and Human Health in a Chinese Megacity (APHH-China)”. The aim is to capture the spatio-temporal variability in people's exposure to fine particles (PM2.5) and black carbon (BC) air pollution in Beijing, China. A total of 120 students were recruited for a panel study from ten universities in Haidian District in northwestern Beijing from December 2017 to June 2018. Real-time personal concentrations of PM2.5 and BC were measured over a 24-h period with two research-grade portable personal exposure monitors. Personal microenvironments (MEs) were determined by applying an algorithm to the handheld GPS unit data. On average, the participants spent the most time indoors (79% in Residence and 16% in Workplace), and much less time travelling by Walking, Cycling, Bus and Metro. Similar patterns were observed across participant gender and body-mass index classifications. The participants were exposed to 33.8 ± 27.8 μg m−3 PM2.5 and to 1.9 ± 1.2 μg m−3 BC over the 24-h monitoring period, on average 24.3 μg m−3 (42%) and 0.8 μg m−3 (28%) lower, respectively, than the concurrent fixed-site ambient measurements. Relative differences between personal and ambient BC concentrations showed greater variability across the MEs, highlighting significant contributions from Dining and travelling by Bus, which involve potential combustion of fuels. This study demonstrates the potential value of personal exposure monitoring in investigating air pollution related health effects, and in evaluating the effectiveness of pollution control and intervention measures.

Advancing systematic-review methodology in exposure science for environmental health decision making.

Systematic review (SR) is a rigorous methodology applied to synthesize and evaluate a body of scientific evidence to answer a research or policy question. Effective use of systematic-review methodology enables use of research evidence by decision makers. In addition, as reliance on systematic reviews increases, the required standards for quality of evidence enhances the policy relevance of research. Authoritative guidance has been developed for use of SR to evaluate evidence in the fields of medicine, social science, environmental epidemiology, toxicology, as well as ecology and evolutionary biology. In these fields, SR is typically used to evaluate a cause-effect relationship, such as the effect of an intervention, procedure, therapy, or exposure on an outcome. However, SR is emerging to be a useful methodology to transparently review and integrate evidence for a wider range of scientifically informed decisions and actions across disciplines. As SR is being used more broadly, there is growing consensus for developing resources, guidelines, ontologies, and technology to make SR more efficient and transparent, especially for handling large amounts of diverse data being generated across multiple scientific disciplines. In this article, we advocate for advancing SR methodology as a best practice in the field of exposure science to synthesize exposure evidence and enhance the value of exposure studies. We discuss available standards and tools that can be applied and extended by exposure scientists and highlight early examples of SRs being developed to address exposure research questions. Finally, we invite the exposure science community to engage in further development of standards and guidance to grow application of SR in this field and expand the opportunities for exposure science to inform environment and public health decision making.

In Vitro Evaluation of Iron-Induced Salivary Lipid Oxidation Associated with Exposure to Iron Nanoparticles: Application Possibilities and Limitations for Food and Exposure Sciences.

Zerovalent iron nanotechnologies are widely used for groundwater remediation and increasingly considered for advance oxidation treatment in drinking water applications. Iron nanoparticles have been detected in drinking water systems and considered for food fortification; therefore, the potential for human exposure through ingestion can be a concern. This study aimed to assess whether ingestion of iron nanoparticles from drinking water could be detected through flavor perception using In Vitro salivary lipid oxidation as an indicator for metallic flavor perception. Ten female subjects, aged 29–59 years, donated saliva samples for use in the In Vitro experiments. Test samples consisted of 1:1 mixture of saliva and bottled drinking water (control) and three treatment solutions, spiked with ferrous sulfate, stabilized zerovalent iron nanoparticles (nZVI), and an aggregated/microsized suspension of mixed zerovalent iron and microsized suspension of iron and iron oxide metal powder, (mZVI). Upon mixing, samples were subjected to 15 min incubation at 37 °C to resemble oral conditions. Salivary lipid oxidation (SLO) was measured in all samples as micromoles of thiobarbituric acid reactive substances (TBARS)/mg Fe. Exposure to iron in all three forms induced significant amount of SLO in all treatment samples as compared to the control (p < 0.0001). The mean SLO levels were the highest in the ferrous treatment, followed by nZVI and mZVI treatments; the differences in the mean SLO levels were significant (p < 0.05). The findings indicate that oral exposure to stabilized ZVI nanoparticles may induce sensory properties different from that of ferrous salt, likely predictive of diminished detection of metallic flavor by humans.

The COVID-19 pandemic: a moment for exposure science.

The COVID-19 pandemic: a moment for exposure science.

COVID-19 Outbreak in Italy: Protecting Worker Health and the Response of the Italian Industrial Hygienists Association.

The number of people infected with severe acute respiratory syndrome—coronavirus 2 (SARS-CoV-2), i.e. the virus causing coronavirus disease (COVID-19), is dramatically increasing worldwide to the size of a pandemic. At the time of writing Italy is ranking first among countries both in terms of number of COVID-19 confirmed cases and in terms of number of deaths. Such a wide spread of COVID-19 has led to concern among workers who are facing the risk of becoming infected during the execution of their duties. We believe it is useful to remark on the need for professional expertise in the field of Occupational Hygiene in this emergency context, in which the indications provided by national and international bodies, the available scientific literature and the legal provisions are constantly and rapidly evolving. It is of fundamental importance that there is an effective analysis of expert inputs, to provide essential guidance to Health, Safety and Environmental managers and other prevention managers in workplaces. In this regard, not only a constant update of the regulatory framework is needed, but also a development and circulation of operational guidance to all the stakeholders to translate general indications into clear operating procedures and implementation tools to be adopted in the workplaces. We believe that the scientific associations in the field of Occupational Hygiene play a crucial role in guiding and assisting prevention professionals. There is considerable expertise in the occupational hygiene and exposure science communities that can help employers and workers to contain and delay the spread of COVID-19. For this reason, the Italian Association of Industrial Hygienists (AIDII—Associazione Italiana degli Igienisti Industriali) published documents containing operational guidelines to provide correct and constantly updated information for: (i) workers employed in essential activities (with low and medium risk of contagion), (ii) health workers and other workers at high or very high risk of contagion, and (iii) for the correct use and handling of personal protective equipment for workers and for the population in general. It is worth pointing out that the documents produced are not intended to replace those produced by authoritative bodies, but to comply with and complete them by reporting an effective summary and further indications about the measures that should be taken in practice under the light of the Italian legislation. At present, the challenge is to produce scientifically sound knowledge, appropriate tools, and effective methodologies, by coordinating the initiatives of different scientific associations, with the final aim to effectively transfer them to employers and workers.

A Next-Generation Risk Assessment Case Study for Coumarin in Cosmetic Products.

Next-Generation Risk Assessment is defined as an exposure-led, hypothesis-driven risk assessment approach that integrates new approach methodologies (NAMs) to assure safety without the use of animal testing. These principles were applied to a hypothetical safety assessment of 0.1% coumarin in face cream and body lotion. For the purpose of evaluating the use of NAMs, existing animal and human data on coumarin were excluded. Internal concentrations (plasma Cmax) were estimated using a physiologically based kinetic model for dermally applied coumarin. Systemic toxicity was assessed using a battery of in vitro NAMs to identify points of departure (PoDs) for a variety of biological effects such as receptor-mediated and immunomodulatory effects (Eurofins SafetyScreen44 and BioMap Diversity 8 Panel, respectively), and general bioactivity (ToxCast data, an in vitro cell stress panel and high-throughput transcriptomics). In addition, in silico alerts for genotoxicity were followed up with the ToxTracker tool. The PoDs from the in vitro assays were plotted against the calculated in vivo exposure to calculate a margin of safety with associated uncertainty. The predicted Cmax values for face cream and body lotion were lower than all PoDs with margin of safety higher than 100. Furthermore, coumarin was not genotoxic, did not bind to any of the 44 receptors tested and did not show any immunomodulatory effects at consumer-relevant exposures. In conclusion, this case study demonstrated the value of integrating exposure science, computational modeling and in vitro bioactivity data, to reach a safety decision without animal data.

Leveraging Existing Cohorts to Study Health Effects of Air Pollution on Cardiometabolic Disorders: India Global Environmental and Occupational Health Hub.

Air pollution is a growing public health concern in developing countries and poses a huge epidemiological burden. Despite the growing awareness of ill effects of air pollution, the evidence linking air pollution and health effects is sparse. This requires environmental exposure scientist and public health researchers to work more cohesively to generate evidence on health impacts of air pollution in developing countries for policy advocacy. In the Global Environmental and Occupational Health (GEOHealth) Program, we aim to build exposure assessment model to estimate ambient air pollution exposure at a very fine resolution which can be linked with health outcomes leveraging well-phenotyped cohorts which have information on geolocation of households of study participants. We aim to address how air pollution interacts with meteorological and weather parameters and other aspects of the urban environment, occupational classification, and socioeconomic status, to affect cardiometabolic risk factors and disease outcomes. This will help us generate evidence for cardiovascular health impacts of ambient air pollution in India needed for necessary policy advocacy. The other exploratory aims are to explore mediatory role of the epigenetic mechanisms (DNA methylation) and vitamin D exposure in determining the association between air pollution exposure and cardiovascular health outcomes. Other components of the GEOHealth program include building capacity and strengthening the skills of public health researchers in India through variety of training programs and international collaborations. This will help generate research capacity to address environmental and occupational health research questions in India. The expertise that we bring together in GEOHealth hub are public health, clinical epidemiology, environmental exposure science, statistical modeling, and policy advocacy.

Omics for Nurse Scientists Conducting Environmental Health Research.

Nurse scientists are ideally positioned to perform environmental health research and it is critical that the role of omics in the complex relationships between environmental exposures and an individual's unique physiology in human health outcomes be appreciated. Importantly, omics can offer nurse scientists a tool to measure exposure, demonstrate molecular phenotypic changes associated with exposure, and potentially uncover mechanisms of exposure-related disease or negative health outcomes. The purpose of this summary is to serve as an overview of omics methodologies for nurse scientists conducting environmental health research and provides future directions of this work as well as exemplar funding opportunities that demonstrate the growing need and interest in this area. The intersection of nursing and exposure science will accelerate the work in environmental health and bring forth translation of research findings into clinical and community practice. Importantly, this information can better help us understand the variation in response to the environment and support environmental health policy change at the local, state, and federal level to improve community health and well-being.

RoB-SPEO: A tool for assessing risk of bias in studies estimating the prevalence of exposure to occupational risk factors from the WHO/ILO Joint Estimates of the Work-related Burden of Disease and Injury

BackgroundThe World Health Organization (WHO) and the International Labour Organization (ILO) are developing joint estimates of the work-related burden of disease and injury (WHO/ILO Joint Estimates). For this, systematic reviews of studies estimating the prevalence of exposure to selected occupational risk factors will be conducted to provide input data for estimations of the number of exposed workers. A critical part of systematic review methods is to assess risk of bias (RoB) of individual studies. In this article, we present and describe the development of such a tool, called the Risk of Bias in Studies estimating Prevalence of Exposure to Occupational risk factors (RoB-SPEO) tool; report results from RoB-SPEO's pilot testing; note RoB-SPEO's limitations; and suggest how the tool might be tested and developed further. MethodsSelected existing RoB tools used in environmental and occupational health systematic reviews were reviewed and analysed. From existing tools, we identified domains for the new tool and, if necessary, added new domains. For each domain, we then identified and integrated components from the existing tools (i.e. instructions, domains, guiding questions, considerations, ratings and rating criteria), and, if necessary, we developed new components. Finally, we elicited feedback from other systematic review methodologists and exposure scientists and agreed upon RoB-SPEO. Nine experts pilot tested RoB-SPEO, and we calculated a raw measure of inter-rater agreement (Pi) for each of its domain, rating Pi < 0.4 as poor, 0.4 ≤ Pi ≥ 0.8 as substantial and Pi > 0.80 as almost perfect agreement. ResultsOur review found no standard tool for assessing RoB in prevalence studies of exposure to occupational risk factors. We identified six existing tools for environmental and occupational health systematic reviews and found that their components for assessing RoB differ considerably. With the new RoB-SPEO tool, assessors judge RoB for each of eight domains: (1) bias in selection of participants into the study; (2) bias due to a lack of blinding of study personnel; (3) bias due to exposure misclassification; (4) bias due to incomplete exposure data; (5) bias due to conflict of interest; (6) bias due to selective reporting of exposures; (7) bias due to difference in numerator and denominator; and (8) other bias. The RoB-SPEO's ratings are low, probably low, probably high, high or no information. Pilot testing of the RoB-SPEO tool found substantial inter-rater agreement for six domains (range of Pi for these domains: 0.51–0.80), but poor agreement for two domains (i.e. Pi of 0.31 and 0.33 for biases due to incomplete exposure data and in selection of participants into the study, respectively). Limitations of RoB-SPEO include that it has not yet been fully performance-tested. ConclusionsWe developed the RoB-SPEO tool for assessing RoB in prevalence studies of exposure to occupational risk factors. The tool will be applied and its performance tested in the ongoing systematic reviews for the WHO/ILO Joint Estimates.