Federal Reserve Board announces approval of application by Taiwan Business Bank
Human biomarkers are comprised of compounds from cellular metabolism, oxidative stress, and the microbiome of bacteria in the gut, genitourinary, and pulmonary tracts. When we examine patterns in human biomarkers to discern human health state or diagnose specific diseases, it is important to under stand which compounds are indeed representative of human metabolism. Inversely, if we are diagnosing an infectious state, then the “fingerprints” of specific pathogens become the important signal. This was the focus of talks by some members of the International Association of Breath Research (IABR) at the PittCon 2014 Conference and Exposition (www.PittCon.org) in Chicago, Illinois during the week of March 1-6. The PittCon meetings have not traditionally included a breath research component, as they are a broad gathering of (mostly) analytical chemists that focus on instrumentation; the attendance is generally around 20,000 conferees, and there are 1,000 or more commercial exhibitors. It has only been in the past five years that breath research has become a regular feature at PittCon meetings.
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Humans are exposed to a large number of environmental chemicals: Some of these may be toxic, and many others have unknown or poorly characterized health effects. There is intense interest in determining the impact of exposure to environmental chemical mixtures on human health. As the study of mixtures continues to evolve in the field of environmental epidemiology, it is imperative that we understand the methodologic challenges of this research and the types of questions we can address using epidemiological data. In this article, we summarize some of the unique challenges in exposure assessment, statistical methods, and methodology that epidemiologists face in addressing chemical mixtures. We propose three broad questions that epidemiological studies can address: a) What are the potential health impacts of individual chemical agents? b) What is the interaction among agents? And c) what are the health effects of cumulative exposure to multiple agents? As the field of mixtures research grows, we can use these three questions as a basis for defining our research questions and for developing methods that will help us better understand the effect of chemical exposures on human disease and well-being.
Citation: Braun JM, Gennings C, Hauser R, Webster TF. 2015. What can epidemiological studies tell us about the impact of chemical mixtures on human health? Environ Health Perspect 124:A6–A9; http://dx.doi.org/10.1289/ehp.1510569.
Address correspondence to J.M. Braun, Department of Epidemiology, Brown University School of Public Health, 121 Main St., Providence, RI 02912 USA. E-mail: Joseph_Braun_1@Brown.edu
Motivation for the ideas in this article arose during the planning process for the National Institute of Environmental Health Sciences (NIEHS) workshop, “Statistical Approaches for Assessing Health Effects of Environmental Chemical Mixtures in Epidemiology Studies.”
We wish to thank the following scientists for facilitating the NIEHS workshop: L.S. Birnbaum, D.J. Carlin, G.W. Collman, C.H. Dilworth, K.A. Gray, J.J. Heindel, B.R. Joubert, C.V. Rider, K.W. Taylor, C.L. Thompson, W. Suk, and R. Woychik. We also thank D.A. Savitz, Brown University, Providence, RI, for his helpful feedback on an earlier draft of this article.
This work was supported by the following NIEHS grants: R00 ES020346, R01 ES024381, P42 ES007381, P30 ES023515, R01 ES009718, and R01 ES022955.
J.M.B. was financially compensated for conducting a re-analysis of a study of child lead exposure for the plaintiffs in a public nuisance case related to childhood lead poisoning that is not directly related to the present study.
The authors declare they have no actual or potential competing financial interests.
Final Publication: 1 January 2016
Biomonitoring studies confirm that humans are exposed to a large number of environmental chemicals across the life span, often simultaneously (CDC 2015; Woodruff et al. 2011). Although there is growing concern that exposure to chemical mixtures during critical periods of human development could increase the risk of adverse health effects including allergic diseases, cancer, neurodevelopmental disorders, reproductive disorders, and respiratory diseases, researchers primarily study chemicals as if exposure occurs individually. This one-chemical-at-a-time approach has left us with insufficient knowledge about the human health effects of exposure to chemical mixtures. Quantifying the risk of disease from environmental chemical mixtures could help identify modifiable exposures that may be amenable to public health interventions.
As interest in chemical mixtures evolves, there is a need for greater involvement of epidemiologists in this area of research (Carlin et al. 2013). We describe some of the unique challenges to studying environmental chemical mixtures in human populations and propose three broad questions related to chemical mixtures that epidemiology can address. We believe this information will help investigators select the best epidemiological and statistical methods for studying chemical mixtures in human populations and consider the limitations of these methods in their studies.
Challenges to Studying Chemical Mixtures
Measuring environmental chemical exposure. Measuring human exposure to a large number of chemicals is a daunting task. First, the study of chemical mixtures requires accurate measurement of the individual components of the mixture. Sensitive and specific exposure biomarkers are one method to assess chemical exposures. These biomarkers have revolutionized the study of chemical mixtures by allowing investigators to directly measure individual chemical concentrations in a variety of biospecimens (Needham et al. 2008). While chemical exposure biomarkers have many strengths, caution should be exercised because of the potential limitations related to misclassification of exposures with high within-person variability (e.g., many short half-life chemicals such as bisphenol A), reverse causality due to pharmacokinetic factors (e.g., excretion) related to the outcome under study (Savitz 2014), or the inability for the biomarker to represent exposure during the etiologically relevant time period.
Second, epidemiologists who study mixtures must consider pragmatic factors when measuring a large number of environmental chemicals. Financial cost is perhaps the most important limiting factor when using biomarker-based approaches to study chemical mixtures because the inclusion of more components in targeted analytical chemistry methods increases the cost, often at the sake of sample size. In addition to cost, the volume of biospecimens (e.g., blood, urine, and plasma) required for these assays and the collection of samples from special populations (e.g., neonates or toddlers) must be considered. The streetlight effect, a type of observational bias, has limited the number of chemicals studied because epidemiologists have typically measured only a few chemicals, choosing from those known to be of concern or those for which measurement methods currently exist. However, advances in analytic chemistry methods (e.g., nontargeted analysis) allow epidemiologists to broaden their scope and identify new or replacement chemicals introduced into commerce and industry.
Some statistical challenges. The risk of false-positive results is a concern when analyzing a large number of exposures. Several statistical methods, including the Bonferroni correction, are used to reduce type I error rates in studies with a large number of hypotheses (Glickman et al. 2014). The Bonferroni approach is an appealing method when dealing with hundreds or thousands of potential hypotheses in studies of mixtures; however, over-reliance on significance testing in observational studies where exposures are not randomized and are often correlated with one another can be problematic (Poole 2001; Rothman 1986, 1990; Savitz 1993). Although hypothesis testing is still used as a method of inference, epidemiologists must also assess the validity, magnitude, and precision of observed associations rather than just the statistical significance of associations.
Type II errors can be equally problematic in studies of chemical mixtures. The statistical power to precisely estimate subtle effects between chemicals and human health may be limited by sample size, the accuracy of exposure assessment methods (e.g., nondifferential exposure misclassification), or multicollinearity issues due to correlations among chemicals in the mixture (i.e., inflated variance estimates) (Cox et al. 2015; Braun et al. 2014).
Confounding due to correlated exposures. While confounding due to socioeconomic factors associated with both the exposure and outcome is almost always considered as a potential source of bias in environmental epidemiology studies, confounding due to correlated copollutants can also exist. For example, in studies of persistent pollutants like polychlorinated biphenyls (PCBs), dioxins, and organochlorine pesticides, exposure biomarkers are often correlated with each other and may also be correlated with health outcomes (Longnecker et al. 2000). Such confounding, depending on the magnitude of correlation between the pollutants, can make identifying the effect of an individual chemical difficult, if not impossible. Thus, it is essential to understand the patterns of environmental exposures in human populations, as well as the correlation between individual agents, to determine if copollutant confounding may be present and whether public health interventions designed to reduce chemical exposures should target the entire mixture or components of it.
Identifying important mixtures. The pattern of human exposure to environmental chemicals is complex and multifactorial. Many pollutants are correlated with each other and some combinations of exposures are more likely than others. Because there is a need to identify patterns of exposure that are most likely to be relevant to human health, some pollutant combinations may be of less relevance if there are no individuals with a given pattern of exposure. Thus, in ranking the importance of these patterns, epidemiologists will need to consider the variability and prevalence of the exposure in the source population, the potential potency of the individual chemical components, and the ability to effectively reduce or mitigate the impact of exposure if adverse health effects are identified.
Lack of standard methods to evaluate environmental mixtures. A variety of statistical methods are available to address questions related to chemical mixtures (Billionnet et al. 2012; Sun et al. 2013), but there is no consensus on standard methods for studying environmental mixtures in epidemiological studies. Although we do not advocate for a formulaic approach, we believe it would be helpful to have a better understanding of the types of mixtures-related questions that epidemiologists can address so that appropriate methods and statistical tools can be selected to adequately address research and public health needs.
Types of Questions Epidemiology Can Address
In this section, we describe three broad questions related to chemical mixtures that epidemiological studies could address; in Table 1, we list examples of how these questions have been addressed using different approaches, as well as the challenges to implementing them.
What are the health effects of individual chemicals within a mixture? The first question epidemiology can address is the association between individual chemical exposures in a mixture and human health outcomes. Because of the large number of environmental agents that humans are exposed to, there is a need to identify exposures that are most strongly associated with adverse health outcomes including individual exposures or groups of highly correlated and related exposures with a common source (e.g., Aroclors of PCB). The results of these studies would help guide public health efforts by allowing us to intervene on those agents that are most likely to be associated with human health.
There are several methods to quantify the association between individual chemical exposures and human health outcomes. An approach taken by many researchers is to quantify the association between each chemical exposure and the health outcome of interest in separate statistical models and then decide which are the most important (Patel et al. 2012). This approach can be extended by accounting for the correlated nature of copollutants and adjusting for potential confounding bias using hierarchical or Bayesian methods (Braun et al. 2014), as well as variable selection techniques such as weighted quantile sum (WQS) regression, elastic net, or least absolute shrinkage and selection operator (LASSO) (Czarnota et al. 2015; Lenters et al. 2015). Because of the correlated nature of many environmental pollutants, it is important to adjust for copollutant confounding using appropriate methods when trying to identify single exposures within a mixture that are most important to human health. Failure to do so could result in attributing one exposure to an adverse health outcome, when it might be due to another correlated copollutant.
What are the interactions between chemicals within a mixture? The second question epidemiological studies can address is whether two or more environmental chemical exposures have a greater than additive (i.e., synergistic) or subadditive (i.e., antagonistic) association with the health outcome of interest. For example, if we examine the risk of disease in relation to two binary exposures, then the standard epidemiological approach to interaction determines if the risk of disease among those exposed to both agents simultaneously is greater than the additive risk among those exposed to each agent individually. Two points are important to consider with interactions: First, even in the absence of a greater than additive interaction between two or more chemicals, joint exposure to these chemicals could have a cumulative effect (Howdeshell et al. 2015). Second, it is critical to note that toxicologists and epidemiologists define interaction differently. For instance, simple concentration-additive effects that are observed in toxicology experiments would be considered synergistic or antagonistic using epidemiological definitions when dose–response curves are nonlinear (Howard and Webster 2013).
Statistically examining interactions between chemicals would help identify synergies or antagonisms between exposures or determine if one or more exposure modifies the effect of other exposures. This could be approached agnostically using variable selection procedures (e.g., LASSO or elastic net) or Bayesian kernel machine regression (Bobb et al. 2015; Sun et al. 2013). Alternatively, a candidate approach could examine interactions between chemicals that act on common biological pathways related to the health outcome of interest. Two primary determinants of our ability to identify interactions will be sample size and the pattern of correlation between exposures. With a fixed sample size, it may be difficult to identify interactions between chemicals because the number of observations will diminish as smaller and smaller strata are examined for each additional chemical-by-chemical interaction considered. In addition, when two or more exposures are highly correlated, there may be an insufficient number of participants with exposure to only one of the agents, thus limiting our ability to examine the impact of only one exposure. Indeed, when exposures are highly correlated, their individual or interactive effects are of less interest because public health interventions aimed at reducing one exposure would likely reduce the other exposures.
What is the health effect of cumulative chemical exposure? A third question estimates the association between cumulative chemical exposure and human health. Here we are trying to quantify the summary effect of a class or multiple classes of exposure. Unlike the question of interaction, we assume that joint exposure to the chemicals does not have a greater than additive effect on the outcome (in the toxicological sense) and that we can meaningfully condense the different exposures into a single summary metric. This may be most appropriate and insightful when the individual components of the mixture act via common biological pathways (e.g., phthalates or dioxins), when the exposure to individual agents is below some threshold of concern [e.g., no-observed-adverse-effect level (NOAEL) or lowest-observed-adverse-effect level (LOAEL)], and when there are individuals whose aggregate exposure is over this threshold.
Summaries of cumulative exposure can include simple summations of the concentration of individual exposures or by weighting them according to their biological potency [e.g., toxic equivalency factors (TEFs) for dioxin-like compounds] (Burns et al. 2011; Safe 1998). Although simple summary measures such as total serum PCB concentrations can be used, they often reflect the individual component with the highest concentration in the mixture (Axelrad et al. 2009). Thus, these summary measures may not accurately capture the cumulative effect of the mixture if the lower concentration components are more potent than the higher concentration ones. As an alternative, more complex weighting approaches can be used when making certain assumptions about the underlying biology of the dose–response relationship (e.g., concentration addition). One limitation to this approach is that epidemiologists will often require toxicological data that quantifies the biological activity of individual components of the mixture (e.g., TEFs for dioxin-like compounds). Furthermore, different health end points (e.g., cancer vs. neurodevelopment) may need different summary measures or weights to accurately describe the cumulative exposure to the mixture.
There are several additional strategies that can be used to estimate the cumulative health effects of a mixture. One could quantify the total biological activity in individual biospecimens through integrative assays (e.g., total estrogenicity) and use it as a measure of exposure (Howard and Webster 2013; Vilahur et al. 2013). These measures have the advantage of capturing both additive and interactive effects. Statistically driven approaches, such as principal components analysis, can identify latent factors that explain the correlation between mixture components. These factors can be used as an exposure variable in statistical models (Maresca et al. 2015). Although principal components methods are advantageous for studying some exposures, particularly those with common sources (e.g., air pollution), the derived factors are difficult to interpret because they are on a dimensionless scale that is not specific to any one chemical exposure, and they may be unique to the population being studied, thus limiting their generalizability. Other methods, including empirically estimated weights, may be used to create weighted sums of standardized concentrations (Czarnota et al. 2015).
By defining the types of research questions related to chemical mixtures that epidemiological studies can address, we hope to identify the gaps in our knowledge and develop or apply appropriate statistical methods that accurately quantify the impact of chemical mixtures on human health. In this article, we have chosen to focus on environmental chemicals, but the three questions we describe naturally extend to other environmental exposures (e.g., air pollution and infectious agents), as well as the broader exposome (e.g., stress and nutrition) (Wild 2005). By examining chemical mixtures, instead of one chemical at a time, we may identify risk factors for diseases with environmental origins and develop more targeted public health interventions.
Bobb JF, Valeri L, Claus Henn B, Christiani DC, Wright RO, Mazumdar M, et al. 2015. Bayesian kernel machine regression for estimating the health effects of multi-pollutant mixtures. Biostatistics 16(3):493–508.
Braun JM, Kalkbrenner AE, Just AC, Yolton K, Calafat AM, Sjödin A, et al. 2014. Gestational exposure to endocrine-disrupting chemicals and reciprocal social, repetitive, and stereotypic behaviors in 4- and 5-year-old children: the HOME study. Environ Health Perspect 122(5):513–520; doi: 10.1289/ehp.1307261.
Carlin DJ, Rider CV, Woychik R, Birnbaum LS. 2013. Unraveling the health effects of environmental mixtures: an NIEHS priority. Environ Health Perspect 121(1):A6–A8; doi: 10.1289/ehp.1206182.
CDC (Centers for Disease Control and Prevention). 2015. Fourth National Report on Human Exposure to Environmental Chemicals. Available: http://www.cdc.gov/biomonitoring/pdf/FourthReport_UpdatedTables_Feb2015.pdf [accessed 25 April 2015].
Claus Henn B, Schnaas L, Ettinger AS, Schwartz J, Lamadrid-Figueroa H, Hernandez-Avila M, et al. 2012. Associations of early childhood manganese and lead co-exposure with neurodevelopment. Environ Health Perspect 120(1):126–131; doi: 10.1289/ehp.1003300.
Cox KJ, Porucznik CA, Anderson DJ, Brozek EM, Szczotka KM, Bailey NM, et al. 2015. Exposure classification and temporal variability in urinary bisphenol-A concentrations among couples in Utah: the HOPE Study. Environ Health Perspect; http://dx.doi.org/10.1289/ehp.1509752.
Czarnota J, Gennings C, Colt JS, De Roos AJ, Cerhan JR, Severson RK, et al. 2015. Analysis of environmental chemical mixtures and non-Hodgkin lymphoma risk in the NCI-SEER NHL study. Environ Health Perspect 123(10):965–970; doi: 10.1289/ehp.1408630.
Howard GJ, Webster TF. 2013. Contrasting theories of interaction in epidemiology and toxicology. Environ Health Perspect 121(1):1–6; doi: 10.1289/ehp.1205889.
Howdeshell KL, Rider CV, Wilson VS, Furr J, Lambright CR, Gray LE Jr. 2015. Dose addition models based on biologically relevant reductions in fetal testosterone accurately predict postnatal reproductive tract alterations by a phthalate mixture in rats. Toxicol Sci; http://dx.doi.org/10.1093/toxsci/kfv196.
Lenters V, Portengen L, Rignell-Hydbom A, Jonsson BA, Lindh CH, Piersma AH, et al. 2015. Prenatal phthalate, perfluoroalkyl acid, and organochlorine exposures and term birth weight in three birth cohorts: multi-pollutant models based on elastic net regression. Environ Health Perspect; http://dx.doi.org/10.1289/ehp.1408933.
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Maresca MM, Hoepner LA, Hassoun A, Oberfield SE, Mooney SJ, Calafat AM, et al. 2015. Prenatal exposure to phthalates and childhood body size in an urban cohort. Environ Health Perspect; http://dx.doi.org/10.1289/ehp.1408750.
Patel CJ, Cullen MR, Ioannidis JP, Butte AJ. 2012. Systematic evaluation of environmental factors: persistent pollutants and nutrients correlated with serum lipid levels. Int J Epidemiol 41(3):828–843.
Sun Z, Tao Y, Li S, Ferguson KK, Meeker JD, Park SK, et al. 2013. Statistical strategies for constructing health risk models with multiple pollutants and their interactions: possible choices and comparisons. Environ Health 12:85; doi: 10.1186/1476-069X-12-85.
Vilahur N, Molina-Molina JM, Bustamante M, Murcia M, Arrebola JP, Ballester F, et al. 2013. Male specific association between xenoestrogen levels in placenta and birthweight. Environ Int 51(1):174–181.
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Due to their antifungal, antibacterial, antiviral, and antimicrobial properties, silver nanoparticles (AgNPs) are used in consumer products intended for use by children or in the home. Children may be especially affected by the normal use of consumer products because of their physiological functions, developmental stage, and activities and behaviors. Despite much research to date, children’s potential exposures to AgNPs are not well characterized. Our objectives were to characterize selected consumer products containing AgNPs and to use the data to estimate a child’s potential non-dietary ingestion exposure. We identified and cataloged 165 consumer products claiming to contain AgNPs that may be used by or near children or found in the home. Nineteen products (textile, liquid, plastic) were selected for further analysis. We developed a tiered analytical approach to determine silver content, form (particulate or ionic), size, morphology, agglomeration state, and composition. Silver was detected in all products except one sippy cup body. Among products in a given category, silver mass contributions were highly variable and not always uniformly distributed within products, highlighting the need to sample multiple areas of a product. Electron microscopy confirmed the presence of AgNPs. Using this data, a child’s potential non-dietary ingestion exposure to AgNPs when drinking milk formula from a sippy cup is 1.53 μg Ag/kg. Additional research is needed to understand the number and types of consumer products containing silver and the concentrations of silver in these products in order to more accurately predict children’s potential aggregate and cumulative exposures to AgNPs.
National Institute of Environmental Health Sciences and National Toxicology Program, National Institutes of Health, U.S. Department of Health and Human Services, Research Triangle Park, North Carolina, USA
Citation: Birnbaum LS. 2016. NIEHS celebrates 50 years of environmental health research at the NIH. Environ Health Perspect 124:A5; http://dx.doi.org/10.1289/ehp.1511015
The author declares she has no actual or potential competing financial interests.
Final Publication: 1 January 2016
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On 1 November 2016 the National Institute of Environmental Health Sciences (NIEHS) will celebrate its 50th anniversary, five decades after the U.S. Surgeon General announced the establishment of the Division of Environmental Health Sciences at the National Institutes of Health (NIH). Today, from its home in Research Triangle Park, North Carolina, the NIEHS funds more than $750 million in research each year to discover how the environment influences human health and disease.
It is my honor and privilege to serve as the NIEHS director during this significant milestone in the institute’s history, and I see it as an opportunity to highlight the improvements to public health that have resulted from environmental science research. I also want to bring together health researchers supported by the NIEHS, and the NIH as a whole, for networking and collaboration. I’m really excited about all the scientific and public outreach activities we’ve planned for the 2016 anniversary year.
This month the NIEHS will hold an oral history event featuring alumni and retirees who will share their reflections on scientific progress, professional experiences, and personal memories at the institute. We’ll also initiate a time capsule and begin collecting nominations for items to fill it so that we can share our 2016 NIEHS research and culture with future staff and science historians.
We’ll host several distinguished lectures at the NIEHS and hear from top scientists, including Gina Turrigiano, Gerard Karsenty, Myles Brown, and Jeff Gordon. All these lectures will be open to the public and webcast live from our website at http://www.niehs.nih.gov.
The NIEHS will partner with the Society of Toxicology in July for a day-long symposium on technological advances, and with the Endocrine Society in September for a three-day workshop on endocrine disruptor research.
A Women’s Health Awareness event at North Carolina Central University, a public forum at the Research Triangle Foundation, and a Science in the Cinema program at Marbles Kids Museum in downtown Raleigh are just a few ways the NIEHS will engage the communities surrounding Research Triangle Park to share information about environmental health and the value of our research.
On the anniversary day of 1 November 2016, hundreds of research partners, grantees, and public health officials will join institute staff and alumni for a very special program celebrating the history, scientific advances, and public health contributions resulting from the unique and prevention-focused research supported by the NIEHS.
Finally, in December, for the first time ever we’ll bring together at once all our grant-funded research center directors and their key scientific staff from across the United States for a lively exchange of research findings, methods, and community engagement practices.
A full calendar of events is posted on the NIEHS website, and I hope our friends and partners will plan to join us often. We’ll also be posting fun and interesting photos and recordings from the past 50 years.
We hope you’ll take the opportunity in 2016 to tell someone you know about the NIEHS and what it has meant to you. I’d love to hear your stories, and I’ll add them to my own, which began 36 years ago when I started my federal research career as a senior staff fellow at the NIEHS.
1Editor-in-Chief and 2Children’s Health Editor, Environmental Health Perspectives, National Institute of Environmental Health Sciences, National Institutes of Health, U.S. Department of Health and Human Services, Research Triangle Park, North Carolina, USA
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EHP’s sixth annual Children’s Health Collection, now online at http://ehp.niehs.nih.gov/special-collections, compiles a year’s worth of research, commentary, and news published from October 2014 through September 2015. From the negative health effects of chemical, physical, and social hazards to the benefits of living in a healthy environment—both natural and built—the Collection tells the story of where we are today and points to the important work that lies ahead. It offers something for everyone concerned about children’s environmental health—researchers, regulators, advocates, health care providers, policy makers, educators, community developers, and parents—and we encourage you to download and share it.
Reflecting upon the latest Collection, we are struck by how quickly the field of children’s environmental health is expanding and evolving, leading to a far more holistic understanding of how diverse environmental factors contribute to a child’s growth and development, from before birth through childhood and into adulthood. We are coming to appreciate the value of research designed to integrate children’s environmental exposures and health determinants across scales, starting with individual- and family-level factors (e.g., what we eat, the products we use, whether to breastfeed or rely on formula), and extending outward to consider community factors (e.g., proximity to pollution sources, access to fresh food and safe outdoor areas, local air and water quality in both urban and rural settings), and, finally, to national and global factors (e.g., climate change and its diverse ramifications for children’s health).
We have long appreciated that the most vulnerable children are often those living in the communities most in need of environmental intervention, but we have lacked effective, coordinated means to fix the problem. Now, with increased attention on community factors that contribute to children’s health and well-being, we are realizing that effective environmental and public health intervention requires the collaborative efforts of decision makers across all sectors of society. Therefore, we need research to inform governmental sectors that act to prevent exposures and risks and to preserve natural environments, commercial sectors that design and repair the built environment and provide safe products, and public health sectors that create policy to prevent and treat childhood diseases. Recent articles focusing on multiple consequences of fracking, the complexity of indoor air pollution, the benefits of walkability in neighborhoods and access to green and blue spaces with respect to reducing obesity and improving neurobehavioral function in children, and how climate change may affect asthma risks illustrate the importance of decisions about the built and natural environments beyond those designed to reduce chemical exposures.
This year’s Collection includes numerous reports based on cohort studies and surveys from around the globe. These involve pregnant women and children in Canada, Mexico, Costa Rica, Brazil, Korea, China, Taiwan, Bangladesh, Tanzania, Belgium, Denmark, Norway, France, Spain, Switzerland, England, Greece, and Yugoslavia, as well as in the United States. Some of these studies, including those under way in the Children’s Environmental and Disease Prevention Research Program funded by the National Institute of Environmental Health Sciences and the U.S. Environmental Protection Agency (U.S. EPA 2015), are longitudinal in nature: They follow children from before birth through early childhood and into school age and adolescence. These and other longitudinal studies are finding associations between early-life exposures and a wide variety of adverse health outcomes, from birth defects and low birth weight to asthma, childhood cancer, neurodevelopmental problems (e.g., autism, attention deficit/hyperactivity disorder, impaired cognitive function), and metabolic problems associated with obesity (e.g., hypertension, diabetes).
Comparing the latest EHP Children’s Health Collection with past Collections, we see a noteworthy transition from an emphasis on a single chemical as it relates to a single disease outcome, to a broader analysis of complex exposures (e.g., measuring multiple chemicals, evaluating both chemical and social stressors) in association with multiple disease outcomes. For example, recent research related to neurodevelopment continues existing lines of research on the adverse effects of metals while expanding to consider effects of cigarette smoke, air pollution, pesticides, phthalates, perfluorinated compounds, and/or organochlorines. Furthermore, given the growing problem of childhood obesity, recent papers have sought associations between a wide range of environmental contaminants and measures of body weight, growth, obesity, hypertension, and diabetes. We also see emerging interest in how placental function may modulate fetal exposures, and how social and behavioral factors (including diet), as well as the child’s microbiome, may influence childhood exposures and responses. As children in cohort studies age, researchers will be able to analyze how cumulative exposures to multiple chemicals and other stressors, both during critical windows of development and collectively, contribute to children’s health as it changes across the life course.
Studies in the 2015 Collection, as in years past, evaluated biomarkers in pregnant women and children, not only in the context of identifying avenues for early-life exposures, but also for characterizing molecular initiating events operating on one or more critical developmental processes in the pathway toward disease. For example, several studies reported changes in DNA methylation of specific genes in association with exposures to metals and cigarette smoke during early development. In addition to increased attention on epigenetic mechanisms of disease causation, we see continued focus on endocrine-mediated developmental effects, and oxidative stress as a common pathway to childhood disease.
Biomonitoring data from national surveys and cohort studies, combined with advances in analytical chemistry, continue to define the maternal and child exposome (the totality of environmental exposures over the life course). The plethora of biomonitoring data, in turn, requires more sophisticated approaches for interrogation and analysis. In response, the children’s environmental health community is calling for international cooperation to build human exposure databases and combine biomarker studies. The ESCAPE (European Study of Cohorts for Air Pollution Effects) (ESCAPE 2014) and NewGeneris (CREAL 2011) programs are combining birth cohorts from across Europe and working toward harmonized data collection and sample processing. This approach not only increases statistical power to detect associations, but also shows how exposures vary from country to country. Related efforts in the United States are under way in the Children’s Health Exposure Analysis Resource (CHEAR) program (NIEHS 2015), which is designed to provide tools for comprehensive children’s exposure assessment and data analysis, and through a new National Institutes of Health initiative called Environmental Influences on Child Health Outcomes (ECHO) (Schmidt 2015), which is designed to support longitudinal birth cohorts, build data and tissue repositories, and develop better analytical tools.
Thus, the year ahead holds great promise for new research, and we invite you to submit your best manuscripts to EHP. Looking ahead to our preparations for the Children’s Health Collection 2016, we also welcome your suggestions for making its presentation ever more informative and useful.
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ESCAPE. 2014. ESCAPE—European Study of Cohorts for Air Pollution Effects: Home [website]. Utrecht, the Netherlands:Utrecht University. Available: http://www.escapeproject.eu/ [accessed 1 December 2015].
NIEHS. 2015. Children’s Health Exposure Analysis Resource (CHEAR) [website]. Research Triangle Park, NC:National Institute of Environmental Health Sciences, National Institutes of Health, U.S. Department of Health and Human Services. Available: http://www.niehs.nih.gov/research/supported/dert/programs/chear/ [accessed 1 December 2015].
Schmidt CW. 2015. Growing a new study: Environmental Influences on Child Health Outcomes. Environ Health Perspect 123(10):A260–A263, doi: 10.1289/ehp.123-A260.
U.S. EPA. 2015. NIEHS/EPA Children’s Environmental Health and Disease Prevention Research Centers [website]. Washington, DC:U.S. Environmental Protection Agency. Available: http://www2.epa.gov/research-grants/niehsepa-childrens-environmental-health-and-disease-prevention-research-centers [accessed 1 December 2015].
1U.S. Environmental Protection Agency, Washington, DC USA; 2U.S. Department of Health and Human Services, Washington, DC USA
Citation: Etzel RA, Howard SN. 2016. Renewing the federal commitment to advance children’s health: the President’s Task Force on Environmental Health Risks and Safety Risks to Children. Environ Health Perspect 124:A3–A4; http://dx.doi.org/10.1289/ehp.1511016
The authors declare they have no actual or potential competing financial interests.
Final Publication: 1 January 2016
PDF Version (166 KB)
Eighteen years ago President William Clinton issued Executive Order 13045 calling for each federal agency to “ensure that its policies, programs, activities, and standards address disproportionate risks to children that result from environmental health risks or safety risks” (Clinton and Gore 1997). As part of this Executive Order, Clinton established the President’s Task Force on Environmental Health Risks and Safety Risks to Children (U.S. EPA 2015a). Today the Task Force, which is cochaired by the U.S. Environmental Protection Agency (EPA) and the U.S. Department of Health and Human Services (HHS), continues its collaborative work and met recently to renew the federal commitment to advance children’s health.
The 14 October 2015 meeting was hosted by EPA Administrator Gina McCarthy and HHS Secretary Sylvia Mathews Burwell. Participants, who included representatives of 20 federal departments, agencies, and offices, reviewed the Task Force’s recent accomplishments and reiterated its important role in accomplishing the goals set out by the Executive Order:
- identify priority risks and issues that can be addressed by interagency efforts;
- develop strategies to protect children’s health;
- recommend and implement interagency actions; and
- communicate information to decision makers for use in protecting children’s environmental health and safety.
One of the major areas of interest for the Task Force is asthma disparities in children. In 2012 the Task Force issued a Coordinated Federal Action Plan to Reduce Racial and Ethnic Asthma Disparities, and its implementation is now well under way (U.S. EPA 2015b). The action plan calls for new policies, community programs, and research to reduce the burden of asthma among minority children and those with family incomes below or near the poverty level.
The plan leverages existing federal resources to address well-known preventable factors that contribute to asthma. For example, HHS, the EPA, and the Department of Housing and Urban Development (HUD) teamed up to encourage coverage of in-home asthma interventions by sponsoring regional asthma summits, which included meetings in Baltimore, Philadelphia, Kansas City, Denver, and Los Angeles. This engagement model brings together state and local entities across sectors to promote a collaborative approach in reducing asthma disparities.
Creation of healthy settings for children is another important focus of the Task Force. HUD is leading an effort involving several federal partners to implement recommendations in the report Advancing Healthy Housing—A Strategy for Action, which showcased initiatives to mitigate unsafe housing conditions and a shortage of safe, affordable housing for low-income families (Healthy Homes Workgroup 2013). A significant advance took place in mid-November 2015 when HUD Secretary Julián Castro announced a proposed rule that would require each public housing agency administering public housing to implement a smoke-free policy (HUD 2015). He was joined by the Surgeon General of the U.S. Public Health Service, Dr. Vivek Murthy, who has made promotion of tobacco-free living one of his highest priorities. More than 700,000 housing units, many with young children, would be affected by this rule (HUD 2015). The period for public comment ends 16 January 2016.
A relatively new workgroup within the Task Force is focusing attention on the impacts of climate change on children’s health. In 2014 the Task Force held a workshop on the emerging issue of the impacts of climate change on children’s health. The workshop helped inform every chapter of the U.S. Global Change Research Program’s forthcoming Climate and Health Assessment (U.S. GCRP 2015). The Task Force also solicited nongovernmental organizations, the public, and state, local, and federal governments to submit stories about actions they are taking to protect children’s health against the impacts of climate change (NIEHS 2015).
Among the inspiring stories collected so far is the May 2015 adoption of a resolution by the California Parent Teacher Association (PTA) Convention that officially declares climate change to be a children’s health issue (CA PTA 2015). The resolution calls for the education of parents on the impacts of climate change on children’s health and future welfare as well as the development of students’ own climate and energy literacy. By adopting this resolution, the state PTA put climate change on the agenda of local chapters throughout the state with the goal of mobilizing more than 800,000 California PTA members.
The Task Force member agencies, including the National Institute of Environmental Health Sciences, the Consumer Product Safety Commission, and the Centers for Disease Control and Prevention, have also worked together in assessing the impact of chemicals in the environment on children. A key achievement of the Task Force has been the identification of cross-agency biospecimen resources to support studies measuring children’s chemical exposures.
Because no single federal agency covers the wide array of issues that affect children’s environmental health, collaboration is essential. The Task Force has proven to be an excellent model for interagency collaboration to protect children’s health by providing a focus on the often overlooked contribution of environmental factors, be they chemical, biological, or social. As representatives of participating agencies reflected in October on their major achievements, they renewed their commitment to working together on important children’s health risks and safety risks. A new work plan to guide the group’s efforts over the next year and into the future is in development and is expected to be finalized in 2016.
CA PTA. 2015. Climate Change Is a Children’s Issue. Sacramento, CA:California State Parent Teacher Association. Available: http://downloads.capta.org/res/ClimateChange_is_a_ChildrensIssue.pdf [accessed 18 November 2015].
Healthy Homes Workgroup. 2013. Advancing Healthy Housing—A Strategy for Action. Washington, DC:U.S. Department of Housing and Urban Development. Available: http://portal.hud.gov/hudportal/documents/huddoc?id=stratplan_final_11_13.pdf [accessed 18 November 2015].
HUD. 2015. Instituting smoke-free public housing. Proposed Rule 24 CFR Parts 965 and 966. Washington, DC:U.S. Department of Housing and Urban Development. Available: http://portal.hud.gov/hudportal/documents/huddoc?id=smoke-freepublichousing.pdf [accessed 18 November 2015].
NIEHS. 2015. Climate Change and Children’s Health Policy Roundup [website]. Research Triangle Park, NC:National Institute of Environmental Health Sciences, National Institutes of Health. Available: http://www.niehs.nih.gov/research/programs/geh/climatechange/policy_roundup/index.cfm [accessed 18 November 2015].
U.S. EPA. 2015a. President’s Task Force on Environmental Health and Safety Risks to Children [website]. Washington, DC:U.S. Environmental Protection Agency. Available: http://www2.epa.gov/children/presidents-task-force-environmental-health-and-safety-risks-children [accessed 18 November 2015].
U.S. EPA. 2015b. Coordinated Federal Action Plan to Reduce Racial and Ethnic Asthma Disparities [website]. Washington, DC:U.S. Environmental Protection Agency. Available: http://www2.epa.gov/asthma/coordinated-federal-action-plan-reduce-racial-and-ethnic-asthma-disparities [accessed 18 November 2015].
U.S. GCRP. 2015. USGCRP Climate and Health Assessment [website]. Washington, DC:U.S. Global Change Research Program. Available: http://www.globalchange.gov/health-assessment [accessed 18 November 2015].
Perfluorinated compounds (PFCs) have been widely used in industrial applications and consumer products. Their persistent nature and potential health impacts are of concern. Given the high cost of collecting serum samples, this study is to understand whether we can quantify PFC serum concentrations using factors extracted from questionnaire responses and indirect measurements, and whether a single serum measurement can be used to classify an individual′s exposure over a one-year period. The study population included three demographic groups: young children (2–8 years old) (N=67), parents of young children (<55 years old) (N=90), and older adults (>55 years old) (N=59). PFC serum concentrations, house dust concentrations, and questionnaires were collected. The geometric mean of perfluorooctane sulfonic acid (PFOS) was highest for the older adults. In contrast, the geometric mean of perfluorooctanoic acid (PFOA) was highest for children. Serum concentrations of the parent and the child from the same family were moderately correlated (Spearman correlation (r)=0.26–0.79, p<0.05), indicating common sources within a family. For adults, age, having occupational exposure or having used fire extinguisher, frequencies of consuming butter/margarine, pork, canned meat entrées, tuna and white fish, freshwater fish, and whether they ate microwave popcorn were significantly positively associated with serum concentrations of individual PFCs. For children, residential dust concentrations, frequency of wearing waterproof clothes, frequency of having canned fish, hotdogs, chicken nuggets, French fries, and chips, and whether they ate microwave popcorn were significant positive predictors of individual PFC serum concentrations. In addition, the serum concentrations collected in a subset of young children (N=20) and the parents (N=42) one year later were strongly correlated (r=0.68–0.98, p<0.001) with the levels measured at the first visits, but showed a decreasing trend. Children had moderate correlation (r=0.43) between serum and dust concentrations of PFOS, indicating indoor sources contribute to exposure. In conclusion, besides food intake, occupational exposure, consumer product use, and exposure to residential dust contribute to PFC exposure. The downward temporal trend of serum concentrations reflects the reduction of PFCs use in recent years while the year-to-year correlation indicates that a single serum measurement could be an estimate of exposure relative to the population for a one-year period in epidemiology studies.
The progression of science is driven by the accumulation of knowledge and builds upon published work of others. Another important feature is to place current results into the context of previous observations. The published literature, however, often does not provide sufficient direct information for the reader to interpret the results beyond the scope of that particular article. Authors tend to provide only summary statistics in various forms, such as means and standard deviations, median and range, quartiles, 95% confidence intervals, and so on, rather than providing measurement data. Second, essentially all environmental and biomonitoring measurements have an underlying lognormal distribution, so certain published statistical characterizations may be inappropriate for comparisons. The aim of this study was to review and develop direct conversions of different descriptions of data into a standard format comprised of the geometric mean (GM) and the geometric standard deviation (GSD) and then demonstrate how, under the assumption of lognormal distribution, these parameters are used to answer questions of confidence intervals, exceedance levels, and statistical differences among distributions. A wide variety of real-world measurement data sets was reviewed, and it was demonstrated that these data sets are indeed of lognormal character, thus making them amenable to these methods. Potential errors incurred from making retrospective estimates from disparate summary statistics are described. In addition to providing tools to interpret “other people’s data,” this review should also be seen as a cautionary tale for publishing one’s own data to make it as useful as possible for other researchers.
Blog Post: CIA’s Top 15 Stories of 2015
The widespread use of copper in treated lumber may result in a potential for human exposure. Due to a lack of information concerning the release of copper from treated wood particles following oral ingestion, the in vitro bioaccessibility of copper from copper-treated wood dust in synthetic stomach fluid (SSF) and DI water was investigated. Copper-containing particles ranging in size from nano-scale to micron-scale were observed by transmission electron microscopy (TEM) in thin sections of these micronized copper-treated wood products. Three copper-treated wood products (liquid alkali copper quaternary and two micronized copper quarternary products) from different manufacturers were incubated in the extraction media. The released copper was then fractionated by centrifugation and filtration through 0.45 μm and 10 kDa filters, respectively. Soluble copper released into isolated fractions was measured using Inductively Coupled Plasma-Optical Emission Spectrometry (ICP-OES). Total copper from each wood product was also determined using microwave-assisted acid digestion of dried wood samples and ICP-OES. The bioaccessible copper released into SSF was between 83 and 90% for all wood types. However, the percent of copper released in DI water was between 14 and 25% for all wood products. These data suggest that copper is highly bioaccessible at the low pH values present in the stomach and may pose a potential exposure risk upon ingestion.
The Lawrence Berkeley National Laboratory Population Impact Assessment Modeling Framework (PIAMF) was expanded to enable determination of indoor PM2.5 concentrations and exposures in a set of 50,000 homes representing the US housing stock. A mass-balance model is used to calculate time-dependent pollutant concentrations within each home. The model includes size- and species-dependent removal mechanisms. The particle model was applied to the housing samples of the Relationship of Indoor, Outdoor, and Personal Air (RIOPA) and The Detroit Exposure and Aerosol Research Study (DEARS) studies to compare model- and measurement-based estimates of indoor PM2.5 of outdoor origin. Model-derived distributions of infiltration factors (ratio of indoor PM2.5 of outdoor origin to outdoor PM2.5) are compared to measurement-based distributions obtained in studies conducted in 11 US cities.
Charles W. Schmidt, MS, an award-winning science writer from Portland, ME, has written for Discover Magazine, Science, and Nature Medicine.
Background image: © RooM the Agency/Alamy
Citation: Schmidt CW. 2016. Beyond a one-time scandal: Europe’s ongoing diesel pollution problem. Environ Health Perspect 124:A19–A22; http://dx.doi.org/10.1289/ehp.124-A19
Published: 1 January 2016
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More than half the European passenger fleet is diesel-powered. Although the European Union has been progressively tightening vehicle emissions for decades, new diesel cars still produce on-road nitrogen oxide emissions that far exceed the current standard. Efforts to reduce diesel emissions would likely make the cars more costly, but experts say it can—and should—be done.
© RooM the Agency/Alamy
In September 2015 Volkswagen officials announced that nearly half a million diesel-powered cars sold by the company in the United States contained an illegal “defeat device” that disables pollution controls on the road. The admission came after the U.S. Environmental Protection Agency (EPA) determined that certain Volks-wagen models complied with the federal emissions standard for nitrogen oxides (NOx) only under laboratory testing conditions.1 Depending on individual driving habits and road conditions, real-world NOx emissions from affected 2.0-L engines could soar to 40 times the U.S. standard of 70 mg/mile, the EPA found. Similarly, emissions from the 3.0-L engines found in sport utility vehicles and larger cars could reach 9 times the standard.2 The scandal has since broadened to an estimated 11 million cars sold mostly in Europe by Volkswagen and subsidiaries Audi and Porsche.3
Diesel vehicles make up just 3% of the cars and pickup trucks driven in the United States, and those containing the illegal device make up less than half a percent of all cars, both diesel and gas-powered, says Allen Schaeffer, executive director of the nonprofit Diesel Technology Forum. From the perspective of health, emissions from cheating Volkswagen passenger vehicles might be too small to matter in the United States because there are so few of the vehicles, according to Gary Bishop, a research associate in the Department of Chemistry and Biochemistry at the University of Denver.
By contrast, more than half of Europe’s passenger fleet is diesel-powered. The scandal therefore has had the added effect of spotlighting the persistent problem of NOx pollution in Europe, where diesel emissions are a major contributor to poor urban air quality. To understand the potential health consequences of the emissions breach, however, one must first understand the risks associated with different components of diesel exhaust.
A Stubborn NOx Problem
NOx, which diesel engines produce at high levels, is a collective term for gases including nitrogen oxide (NO) and nitrogen dioxide (NO2). NO has relatively minor health impacts at environmental levels. NO2, however, produces health effects ranging from mild cough and mucous membrane irritation to severe exacerbation of lung conditions such as chronic obstructive pulmonary disease and asthma.4
A November 2015 report by the European Environment Agency (EEA) estimated that 8–12% of Europe’s population is exposed to levels of NO2 that exceed the World Health Organization’s air quality guideline of 40 µg/m3.4 The highest levels were measured near highways, where diesel vehicles contribute about 80% of traffic-related NOx emissions.4 Diesel exhaust is also associated with other air pollutants. Among them are ground-level ozone (O3), which forms when NO2 molecules interact with oxygen in the presence of sunlight, and fine sooty particulates measuring 2.5 µm or less (PM2.5) in the exhaust stream. These pollutants can travel deep into the lungs and elevate risks for DNA damage, heart attacks, and premature death.5,6,7
Urban NO2 exposures can have dire consequences, contributing to an estimated 75,000 premature deaths throughout the European continent in 2012. Ground-level O3 exposures, meanwhile, contributed to an estimated 17,000 premature deaths, and 432,000 premature deaths were attributed to PM2.5. But unlike NO2—which derives mainly from diesel emissions— O3 comes from a wide number of sources besides NO2–sunlight interaction. Similarly, PM2.5 is also released by agriculture, industrial facilities, home heating, and other processes.8
Belching clouds of exhaust, earlier diesel engines lacked the technologies that have lowered PM emissions by more than 90% since they came into widespread use in Europe and the United States during the 1990s.9 These advanced emission controls comprise what’s known as clean diesel technology, which also includes cleaner fuels.10 Schaeffer says clean diesel optimizes low emissions, fuel efficiency, and performance. Its emissions may also be less harmful than emissions from older diesel vehicles.
Animal studies of unfiltered diesel exhaust conducted prior to the emergence of this newer technology found evidence suggestive of carcinogenicity,11 and in 2012 diesel engine exhaust was listed as a Group 1 (i.e., confirmed) human carcinogen by the International Agency for Research on Cancer, based in part on occupational findings of lung cancer in exposed truck drivers and miners.12 Studies published in 2015, however, showed no evidence of carcinogenicity in rats exposed in the laboratory to diesel exhaust that meets the EPA’s more stringent 2007 and 2010 emissions standards, suggesting it may pose a lesser cancer risk to humans.11,13,14
However, these same studies found evidence of abnormalities other than tumors, including mild lung inflammation, oxidative stress, decreased pulmonary function, and histological changes at the highest exposure levels. According to the authors, these effects were consistent with effects observed previously in rats exposed chronically to NO2.13
Europe’s rise in diesel cars is rooted in well-intentioned efforts by national governments to reduce carbon emissions from the transportation sector. Countries that signed the Kyoto Protocol agreed to mandated greenhouse gas reduction targets, which could be met in the manner of their choosing.25 Perceiving an opportunity to meet these targets relatively cheaply, EU countries incentivized the purchase of diesel cars with tax breaks on diesel fuel.26 Unlike gasoline-powered engines that combust fuel with a spark plug, diesel engines compress fuel until it undergoes a controlled explosion. They’re more efficient than gasoline-powered engines, says Allen Schaeffer of the Diesel Technology Forum, and the resulting fuel savings correlate with reduced emissions of carbon dioxide, the principal greenhouse gas implicated in climate change. Subsequently, the percentage of diesel cars in the European passenger fleet shot up, in some countries quadrupling over the next 14 years.27
Balancing PM and NO2
Assessing human health risks from diesel emissions on the basis of NOx measures alone is challenging. That’s because European Union (EU) and U.S. NOx standards don’t distinguish between the NO and NO2 constituents of emissions. Furthermore, depending on the NOx emission control systems used, vehicles emit NO and NO2 in different proportions.
NOx emissions from earlier diesel engines were dominated by NO, says S. Kent Hoekman, a research professor at the Desert Research Institute in Reno, Nevada. But catalytic emissions control systems adopted to meet increasingly stringent NOx standards in the 1990s had the effect of altering this ratio: These systems tend to emit proportionately higher levels of NO2, especially when they don’t work correctly, even as they limit overall NOx emissions.15 Multiple systems are engaged in selectively removing NOx from exhaust streams, Hoekman says, and failure of any one system can lead to higher emissions.
As in the United States, EU regulators have traditionally relied on laboratory testing to evaluate whether diesel vehicles are meeting emissions reduction standards. Yet according to multiple sources interviewed for this story, EU regulators and automakers alike acknowledge that laboratory emissions and on-road emissions aren’t the same. Jens Borken-Kleefeld, a senior researcher with the International Institute for Applied Systems Analysis, explains that laboratory emissions and real-world emissions are instead assumed to be proportional to each other, such that mandated reductions in the laboratory will be met with comparable reductions on the road, although the absolute numbers won’t match. That’s true for both diesel and gasoline cars, he adds.
“This in itself would be satisfactory if real-driving and test-cycle emissions would decrease in tandem,” Borken-Kleefeld says. “But while test-cycle NOx emissions have decreased by 80% since 1992, the real-driving NOx emissions from diesel cars have actually increased by 20% over the same period.”16 The billion-dollar question, he says, is why such high on-road NOx emissions have been allowed to persist for so long.
The EU has been progressively tightening vehicle emissions for decades, from its Euro 1 standard for passenger vehicles, which came into effect in 1991, through the Euro 6 standard for light passenger and commercial vehicles, adopted in 2014.17 But Borken-Kleefeld says that while PM emissions declined sharply as the standards became more stringent, real-world NOx emissions never fell until the Euro 6 standard was adopted. Even now, he says, new diesel cars have real-world NOx emissions that are 4–7 times higher than the current standard of 80 mg/km, although he points out that Euro 5 diesel cars produced, on average, twice that amount.
In the wake of the Volkswagen scandal, EU countries (and officials in the United States and elsewhere) have pledged to shift quickly from laboratory-based to roadside emissions testing, although important testing parameters are still being determined. The EU’s roadside testing regimen will phase in over the next few years, but until 2020 new diesel cars will still be allowed to emit NOx at levels a little over twice the EU standard; after that, they may emit levels 50% higher than the standard.18 But Borken-Kleefeld says Europe could still eliminate almost all its NO2 exceedances by 2030 if diesel cars stay within the Euro limits and if other NOx sources—for instance, trucks, power plants, and residential heating—continue to ratchet down their emissions.19
The Current Situation in Europe
The Volkswagen scandal occurred in a year when air pollution in European cities was making headlines. In mid-March 2015 a dense smog cloud hung over cities in the United Kingdom, France, Spain, Germany, Italy, Poland, and Lithuania.20 The cloud comprised diesel exhaust pollutants and emissions from other sources, including ammonia-based particles generated from the application of manure fertilizers in agriculture, according to Julia Poliscanova, the clean vehicles and air quality officer for the European nonprofit Transport and Environ-ment.For a brief period during that episode Parisian air pollution levels were worse than in any other city in the world, even Beijing and Delhi.21 Generally speaking, the country with the continent’s worst air pollution problem is Italy, where exposures to PM2.5, O3, and NO2 contributed to an estimated 59,500, 21,600, and 3,300 premature deaths, respectively, in 2012.4
Just how much early mortality can be blamed specifically on diesel pollution in Europe isn’t easy to gauge, however. According to the EEA, air quality in Europe overall is improving, even as PM2.5, ground-level O3, and NO2 levels associated with diesel exhaust remain stubbornly high.4 As noted previously, these pollutants have many sources, and their relative contributions to overall air pollution hinge on the complexities of atmospheric chemistry. For instance, NO in diesel exhaust reacts with O3 and destroys it at the tailpipe, which is why the highest O3 levels in Europe tend to be found in the countryside, whereas NO2 tends to peak in the urban core.4
As for the United States, a team of investigators from the Massachusetts Institute of Technology and Harvard University published an analysis suggesting that 59 people might die from the additional pollution emitted by Volkswagen’s cheating diesel vehicles. The authors attributed 87% of those deaths to PM2.5 formed when NOx is converted to secondary ammonium nitrate particles in the atmosphere. The other 13% were attributed to the effects of ground-level O3, with none attributed specifically to NO2. However, the authors note a number of uncertainties in the models they used, which further research may help clarify.22
Meanwhile, in a growing trend, city officials throughout the EU are creating low-emission zones designed to keep older, more-polluting diesel and gasoline vehicles out of certain urban areas.23 Entry into the more than 70 low-emission zones established in Germany, for instance, depends on the color of a sticker mounted on the windshield. Red stickers denote old vehicles with more restricted access, while yellow and green stickers denote newer diesel- and gasoline-powered cars that can enter the zones more often.
Paris and London are following suit with similar approaches. On 27 September 2015 officials in Paris imposed the first-ever “car-free day” in 30% of the city between the hours of 11:00 a.m. and 6:00 p.m. The Guardian newspaper quoted one resident as saying, “The sky has never been this blue. It really is different without a hazy layer of pollution hanging in the air.”24
According to Borken-Kleefeld, however, low-emission zones have not been effective at reducing NO2 concentrations so far. That’s because virtually all new diesel cars that came on the market prior to Euro 6 emitted as much NOx as previous generations, if not more. He predicts that only when new diesel cars with much lower emissions become widespread—within the next 10 years—or when gasoline-powered cars outnumber diesel cars will NO2 exceedances disappear.
Efforts to reduce NO2 emissions from passenger cars will make diesel technology more costly, says Poliscanova. This is especially true in the small market segment, she says, which will raise the attractiveness of cleaner gasoline hybrids.
But in the meantime, Poliscanova argues that urban air in much of Europe is barely fit to breathe, and diesel vehicles are the principal cause. “We’re not calling for the end of diesel,” she says. “But the technology must be clean if it is to be used in the future.”
1. Shinkman S. Re: Notice of Violation to Geanacopoulos D, et al. [letter]. Washington, DC:Office of Civil Enforcement, U.S. Environmental Protection Agency (2 November 2015). Available: http://www2.epa.gov/sites/production/files/2015-11/documents/vw-nov-2015-11-02.pdf [accessed 14 December 2015].
2. EPA. Frequent Questions about Volkswagen Violations [website]. Washington, DC:U.S. Environmental Protection Agency (updated 25 November 2015). Available: http://www.epa.gov/vw/frequent-questions-about-volkswagen-violations [accessed 14 December 2015].
3. Volkswagen. Volkswagen AG Has Issued the Following Information [press release]. Wolfsburg, Germany:The Volkswagen Group (22 September 2015). Available: http://www.volkswagenag.com/content/vwcorp/info_center/en/news/2015/09/Volkswagen_AG_has_issued_the_following_information.html [accessed 14 December 2015].
4. EEA. Air Quality in Europe—2015 Report. EEA Report No. 5/2015. Copenhagen, Denmark:European Environment Agency, European Union (30 November 2015). Available: http://www.eea.europa.eu/publications/air-quality-in-europe-2015 [accessed 14 December 2015].
5. Mills NL, et al. Adverse cardiovascular effects of air pollution. Nat Clin Pract Cardiovasc Med 6(1):36–44 (2009), doi:10.1038/ncpcardio1399.
6. Jantzen K, et al. Oxidative damage to DNA by diesel exhaust particle exposure in co-cultures of human lung epithelial cells and macrophages. Mutagenesis 27(6):693–701 (2012), doi: 10.1093/mutage/ges035.
7. ARB. Diesel & Health Research [website]. Sacramento, CA:Air Resources Board, California Environmental Protection Agency (updated 21 June 2011). Available: http://www.arb.ca.gov/research/diesel/diesel-health.htm [accessed 14 December 2015].
8. EEA. Premature Deaths Attributable to Air Pollution [website]. Copenhagan, Denmark:European Environment Agency, European Union (30 November 2015). Available: http://www.eea.europa.eu/media/newsreleases/many-europeans-still-exposed-to-air-pollution-2015/premature-deaths-attributable-to-air-pollution [accessed 14 December 2015].
9. Herner JD, et al. Effect of advanced aftertreatment for PM and NOx control on heavy-duty diesel truck emissions. Environ Sci Technol 43(15):5928–5933 (2009), doi: 10.1021/es9008294.
10. EPA. Learn About Clean Diesel [website]. Washington, DC:U.S. Environmental Protection Agency (updated 24 September 2015]. Available: http://www.epa.gov/cleandiesel/learn-about-clean-diesel [accessed 14 December 2015].
11. Hallberg LM, et al. Part 3. Assessment of genotoxicity and oxidative damage in rats after chronic exposure to new-technology diesel exhaust in the ACES bioassay. Res Rep Health Eff Inst (184):87–105; discussion 141–171 (2015), PMID: 25842617.
12. IARC. Diesel and Gasoline Engine Exhausts and Some Nitroarenes. IARC Monographs on the Evaluation of Carcinogenic Risks to Humans, Vol. 105. Lyon, France:International Agency for Research on Cancer, World Health Organization (2014). Available: http://monographs.iarc.fr/ENG/Monographs/vol105/mono105.pdf [accessed 14 December 2015].
13. McDonald JD, et al. Part 1. Assessment of carcinogenicity and biologic responses in rats after lifetime inhalation of new-technology diesel exhaust in the ACES bioassay. Res Rep Health Eff Inst (184):9–44; discussion 141–171 (2015), PMID: 25842615.
14. Bemis JC, et al. Part 2. Assessment of micronucleus formation in rats after chronic exposure to new-technology diesel exhaust in the ACES bioassay. Res Rep Health Eff Inst (184):69–82; discussion 141–171 (2015), PMID: 25842616.
15. Boulter PG, et al. The evolution and control of NOx emissions from road transport in Europe. In: Urban Air Quality in Europe (Viana M, ed.). Hdb Env Chem 26:31–54 (2013), doi: 10.1007/698_2012_162.
16. Weiss M, et al. On-road emissions of light-duty vehicles in Europe. Environ Sci Technol 45(19):8575–8581 (2011), doi: 10.1021/es2008424.
17. ACEA. Euro Standards [website]. Brussels, Belgium:European Automobile Manufacturers Association (2015). Available: http://www.acea.be/industry-topics/tag/category/euro-standards [accessed 14 December 2015].
18. European Commission. Commission Welcomes Member States’ Agreement on Robust Testing of Air Pollution Emissions by Cars [press release]. Brussels, Belgium:European Commission, European Union (28 October 2015). Available: http://europa.eu/rapid/press-release_IP-15-5945_en.htm [accessed 14 December 2015].
19. Kiesewetter G, et al. Modelling NO2 concentrations at the street level in the GAINS integrated assessment model: projections under current legislation. Atmos Chem Phys 14(2):813–829 (2014), doi:10.5194/acp-14-813-2014.
20. Mathiesen K. UK issues health warnings as smog cloud spreads across Europe. The Guardian, Environment section, Pollution subsection (19 March 2015). Available: http://www.theguardian.com/environment/2015/mar/19/uk-issues-health-warnings-as-smog-cloud-spreads-across-europe [accessed 14 December 2015].
21. Malykhina L. Paris briefly tops world charts for air pollution. France 24, France section, Pollution subsection (20 March 2015). Available: http://www.france24.com/en/20150320-paris-city-smog-pollution-plume-labs-hidalgo-public-transport-diesel [accessed 14 December 2015].
22. Barrett SRH, et al. Impact of the Volkswagen emissions control defeat device on US public health. Environ Res Lett 10(11):114005 (2015), doi: 10.1088/1748-9326/10/11/114005.
23. CLARS. Urban Access Regulation in Europe [website]. Charging, Low Emission Zones, and Other Access Regulation Schemes; European Commission; European Union (2015). Available: http://urbanaccessregulations.eu/ [accessed 14 December 2015].
24. Chrisafis A. All-blue skies in Paris as city centre goes car-free for first time. The Guardian, World section, Europe subsection (27 September 2015). Available: http://www.theguardian.com/cities/2015/sep/27/all-blue-skies-in-paris-as-city-centre-goes-car-free-for-first-time [accessed 14 December 2015].
25. UNFCCC. Focus: Technology [website]. Bonn, Germany:United Nations Framework Convention on Climate Change (2015). Available: http://unfccc.int/focus/technology/items/7000.php [accessed 14 December 2015].
26. Transport & Environment. Briefing: Fuel and Carbon Taxation in the EU. Brussels, Belgium:Transport & Environment (June 2010). Available: http://www.transportenvironment.org/sites/te/files/media/2010_06_briefing_energy_taxation.pdf [accessed 14 December 2015].
27. EEA. Dieselisation in the EEA [website]. Copenhagen, Denmark:European Environment Agency, European Union (updated 20 October 2015). Available: http://www.eea.europa.eu/data-and-maps/figures/dieselisation-in-the-eea [accessed 14 December 2015].
Event-based precipitation samples were collected at a downtown industrial and a predominantly upwind rural location in the Cleveland, Ohio metropolitan area from July 2009 through December 2010 to investigate the potential local total mercury (Hg) wet deposition enhancement in a region with a high concentration of coal combustion sources. Total Hg wet deposition for the 18-month period was 6.8 μg m−2 (n = 81) at the rural site and 10.7 μg m−2 (n = 98) at the urban site demonstrating a significant (p = 0.046) 37% enhancement in deposition between the two sites. Large deposition events (>0.2 μg m−2) occurred predominantly from May through October (n = 16 (urban), n = 10 (rural)) and represented from 2 to 8% of total 18-month deposition per event. At the downtown urban site, the average Hg precipitation concentration was 53% higher for these large deposition events. Concurrently measured precipitation events delivered in aggregate 2.4 times more total Hg wet deposition to the urban site compared to the rural site. Hg rainfall concentrations for concurrent events with similar precipitation depth were 2–4 times higher at the urban site and suggest scavenging of local Hg emissions. Further evaluation of these events revealed 83% more total Hg deposition at the urban site from January to December 2010 compared to July to December 2009, while there was 26% more at the rural site during these same time periods. The larger increase in deposition at the urban site in 2010 may be evidence of increased local emissions from sources that were known to be offline during this study period because of an economic recession.
In the early 1970s, coal workers’ pneumoconiosis, or black lung, affected around one-third of long-term underground miners. After new dust regulations took effect, rates of black lung plunged. Today, however, they are once again rising dramatically, and the new generation of black lung patients have disease that progresses far more rapidly than in the past.
© Tyler Stableford/Getty
A section of lung shows the ravages of progressive massive fibrosis (PMF). The disease is characterized by large, dense masses of fibrous tissue that often appear in the upper lungs. The lung itself can appear black due to the slow buildup of coal dust particles over the years.
© Biophoto Associates/Getty
Highly reactive particles of coal mine dust can infiltrate the deepest reaches of the lung. These inhaled particles of coal dust and/or silica create a chronic inflammatory response that damages the lung.
© Ed Reschke/Getty
The Coal Workers’ Health Surveillance Program was created in the early 1970s under the Coal Act. Miners who participate in the voluntary program receive an X ray upon being hired, then may return for followup X rays every five years. In the mid-2000s, doctors participating in this program alerted federal authorities to the resurgence of black lung among coal miners in Appalachia.
© Michael Sullivan/Science Source
In 1974, shortly after the Coal Act went into effect, PMF affected nearly 3.5% of coal miners with 25 or more years of underground mining tenure. Rates dropped precipitously under the new protective rules but have since rebounded, shooting up 900% over the past 15 years.
Source: Blackley et al. (2014)7
Background image: Arthur Rothstein/Library of Congress
Carrie Arnold is a freelance science writer living in Virginia. Her work has appeared in Scientific American, Discover, New Scientist, Smithsonian, and more.
Citation: Arnold C. 2016. A scourge returns: black lung in Appalachia. Environ Health Perspect 124:A13–A18; http://dx.doi.org/10.1289/ehp.124-A13
Published: 1 January 2016
Once a month, a group of men in t-shirts, jeans, and baseball caps gather around a long table at the New River Health Clinic. The clinic, a small, one-story yellow clapboard building, is located in the tiny town of Scarbro, nestled in the bituminous hills of southern West Virginia. The members of the Fayette County Black Lung Association greet each other by name while they pour bitter black coffee into small Styrofoam cups.
Amidst the chatter and the coffee are the coughs. Some of the men hack loudly, others more quietly. All of them have advanced black lung, a disease they acquired working in the local mines. Although roughly 22% of underground miners smoke,1 compared with about 18% of U.S. adults in general,2 none of these men do. They gather not just as a support group but also to help one another complete the stacks of paperwork necessary to apply for government-mandated benefits for black lung and navigate the tortuous appeals process.
Aside from the group’s leader, a bespectacled septuagenarian named Joe Massie, all the other members are in their 50s or early 60s. That’s relatively young for someone with advanced black lung, and other workers are getting sick even earlier. These miners, who have gotten so sick so fast, are on the forefront of a wave of new black lung cases that are sweeping through Appalachia.
Scientists first noticed a troubling trend in 2005, when national surveillance conducted by the National Institute for Occupational Safety and Health (NIOSH) identified regional clusters of rapidly progressing severe black lung cases, especially in Appalachia.3 These concerns were confirmed in followup studies using a mobile medical unit providing outreach to coal mining areas,4,5 with later research showing that West Virginia was hit particularly hard.6 Between 2000 and 2012, the prevalence of the most severe form of black lung rose to levels not seen since the 1970s,7 when modern dust laws were enacted.8
Scarier still, the new generation of black lung patients have disease that in many cases progresses far more rapidly than in previous generations. Today, advanced black lung can be acquired within as little as 7.5–10 years of beginning work, says Edward Petsonk, a pulmonologist at West Virginia University. But not all cases progress so quickly; thus, occupational health researchers fear that what they are seeing now is only the tip of the iceberg.
The History of Black Lung
Black lung is not a new disease. Ever since humans first started mining coal nearly 5,000 years ago in Bronze Age China,9 those who worked in the mines breathed in the black dust that, over time, destroyed their lungs.
Writing in 1846, Scottish physician Archibald Makellar sketched out the course of the disease in miners exposed to extremely high levels of dust: “A robust young man, engaged as a miner, after being for a short time so occupied, becomes affected with cough, inky expectoration, rapidly decreasing pulse, and general exhaustion. In the course of a few years, he sinks under the disease; and, on examination of the chest after death, the lungs are found excavated, and several of the cavities filled with a solid or fluid carbonaceous matter.”10 Makellar called the disease “black phthisis.” Later physicians gave black lung its official modern name of coal workers’ pneumoconiosis (CWP).
The disease starts with dust—whether swinging picks or using large machines, the process of breaking up coal and extracting it from its prehistoric home creates vast amounts of dust. And unless effective measures are used to control airborne dust in the narrow underground shafts, miners can breathe it into their lungs.
Coal mine dust isn’t uniform; it’s a jumble of substances and particle sizes, which vary in their effects on the lungs.11 Larger “thoracic” particles settle in the bronchi, the main air passages to the lungs.12 The presence of coal mine dust in the bronchi stimulates the production of mucus, Petsonk explains, so that people can more easily cough up the offending particles. It’s an efficient system, but prolonged inhalation of the dust can lead to chronic bronchitis in miners. “Coal dust particles are very reactive, including the chemical bonds on the surface,” Petsonk explains. “They will interact with anything nearby, including the body’s tissue, which creates an inflammatory response.”
It’s the smaller respirable dust particles, though, that create the damage most associated with CWP. Because of their small size—often 2.5 microns or less in diameter—they can easily travel beyond the bronchi, into the bronchioles and alveoli. Any small particle this deep in the lungs, whether from cigarette smoke, car exhaust, or coal mine dust, can create irritation in the site where it lands.13 The body’s immune system attacks the particles, creating inflammation in the surrounding region. Although this inflammation can help kill invading pathogens, it can’t remove components of coal mine dust such as coal and silica, which remain in place and cause lung tissue damage. The body then doubles down on its efforts, which further damages the delicate lung tissue. The result is chronic inflammation that ultimately scars the lungs, creating patches that radiologists can see on X rays and CT scans.14
Smaller patches of damage may have relatively little effect on a miner’s lung function measurements. Over time, however, the damage becomes more widespread, creating the 1- to 2-mm nodules of immune and inflammatory cells, collagen fibers, and black dust indicative of so-called simple CWP.15 Symptoms of simple CWP include chronic cough, increased phlegm production, and shortness of breath. CWP sufferers also are at increased risk of emphysema,16 which is an important cause of morbidity among miners.17
In some patients, the disease progresses to complicated CWP, a condition also known as progressive massive fibrosis (PMF). As its name suggests, PMF is characterized by large, dense masses of fibrous tissue more than 1 cm in diameter, which often appear in the upper lungs.18 The lung itself often appears blackened. The presence of fibrosis impairs the ability of the lungs to bring oxygen to the blood, which leaves sufferers chronically short of breath and may result in death.6
Initially, coal dust itself was seen as rather harmless, and the true cause of CWP was believed to be silicosis. This disease is caused by inhaling particles of respirable crystalline silica, which also can be found in coal mine dust.19 Indeed, the symptoms of CWP overlap with those of silicosis; the two diseases can look similar on X rays, and both fall within the constellation known as coal mine dust lung disease.18,19 However, work begun in the nineteenth century by Makellar10 and fellow Scottish physician J.C. Gregory,20 which continued into the 1920s and ’30s, began to focus specifically on coal dust as the sole culprit of CWP.21,22 By the 1950s, scientists had shown with near certainty that CWP could be caused exclusively by excessive exposure to coal dust.
This came as no surprise to the tens of thousands of coal miners working throughout Appalachia and across the rest of the country, who for decades had observed and experienced the devastation caused by black lung. By the late 1960s, the crisis had come to a head. In 1968 the members of United Mine Workers of America went on strike to create better working conditions, including protection from coal mine dust, and to set up a fund for miners disabled by black lung.23
The strike worked. In 1969 Congress passed the Federal Coal Mine Health and Safety Act, or Coal Act for short, which was signed into law by President Richard Nixon.24 The Coal Act created the agency that would become the Mine Safety and Health Administration, and required that every underground coal mine be inspected four times per year and surface mines twice a year. The Act also set limits on the amount of dust that miners could be exposed to and developed procedures for miners disabled by CWP to receive compensation.
In the early 1970s, shortly after the Coal Act went into effect, CWP affected around one-third of miners who had worked underground for more than 25 years.5 As the new rules and regulations took effect, rates of CWP began to drop, then plunge. By the 1990s, it seemed CWP was on its way to becoming a thing of the past.25
Fighting the Dust
Another requirement of the Coal Act was the creation of the Coal Workers’ Health Surveillance Program (CWHSP), a voluntary screening program for black lung in which miners receive X rays upon hiring and then can return for followup every five years thereafter. One of the physicians responsible for evaluating those X rays was Petsonk. After the number of miners diagnosed with CWP began to drop in response to the improved dust standards,25 Petsonk expected they would keep dropping—except they didn’t. In the early 2000s, Petsonk believed he was seeing an increase in the number of PMF cases, but he needed data to back up his perception.
In 2005 he and other NIOSH investigators published the initial evidence of geographical clusters of rapidly progressing cases of CWP, including in Appalachia.3 In 2011 Petsonk and colleagues published a study of 138 West Virginia miners compensated by the state for PMF between 2000 and 2009.6 All those miners had spent their careers in the mines long after the Coal Act went into effect. The study thus indicated that either the Coal Act standards were not adequate or the rules were not being followed, or both.
“The only thing that causes this illness is the inhalation of dust during coal mining,” says David Weissman, director of the Respiratory Health Division at NIOSH. “To have people getting sick so young, they must have been way overexposed, which means failures in [regulatory] compliance.”
The black lung data coming in from NIOSH’s screening programs indicated that the rise in CWP was most severe in Kentucky, Virginia, and West Virginia,26 and that miners working in small operations (fewer than 155 miners) were more likely to be affected than those from larger outfits.27 Compared with miners in other states, these miners were also younger, had worked in underground mines for fewer years, and were more likely to have PMF, the most severe form of black lung.27 Another study indicated that abnormal lung function, as measured by spirometry, was three times more prevalent than CWP, suggesting that CWP was not the only disease affecting miners’ lungs.1
The screening program is voluntary, and because less than one-third of miners are estimated to participate.28 NIOSH researchers conducted further analyses to test the robustness of their initial results. The results of these analyses, reported in 2014, indicated that the original estimates of CWP prevalence among coal miners likely did not overstate and may in fact have understated the true prevalence of black lung.29
PMF had become nearly nonexistent in 2000, affecting only 0.08% of CWHSP participants and 0.33% of miners who had worked at least 25 years belowground.7 But as investigators from NIOSH and the Centers for Disease Control and Prevention mapped the prevalence of PMF moving forward, they found a steep U-shaped curve. By 2012, they reported, the prevalence had jumped 900% compared with 2000, affecting 3.23% of miners with 25-plus years of work.7 “These were levels we hadn’t seen since the early 1970s, shortly after modern dust control measures came into effect,” says coauthor David Blackley, an epidemiologist at NIOSH.
For the NIOSH scientists, perhaps the most frustrating part of seeing these numbers was knowing it didn’t have to be this way. “Coal workers’ pneumoconiosis is an entirely preventable disease. They wouldn’t have gotten sick without inhaling way too much coal dust,” says NIOSH coauthor A. Scott Laney.
To the miners of the Fayette County Black Lung Association, the resurgence was no mystery. According to Terry Lilly, a tall, broad-shouldered miner with a gray mustache, weakening of the coal miners’ union in the 1980s undermined the protections put in place by the Coal Act, leaving workers vulnerable. Lilly, who worked as a foreman, says coal mine officials instructed him to alter measurements of dust levels in the mines.
“We knew when the mine inspectors were coming before they even set foot belowground. They’d call us and let us know we had a visitor, and we’d get to work. We’d place dust monitors below vents, where they’d constantly get fresh air. We’d throw up curtains,” Lilly says. And when the dust got too thick, his choice was to continue working or lose his job. Several decades ago, when the unions were stronger, he’d felt empowered to halt operations in unsafe situations, he says, but those days were long gone.
The mining companies under which the violations occurred have been sold or gone bankrupt, and representatives were unavailable to comment for this story. However, says Luke Popovich, a spokesman for the National Mining Association, “No one in this industry wants a mining accident and consequently do not tell their employees to ignore safety standards for any reason.”
Jason Hayes, associate director for the American Coal Council, adds, “I can’t comment on any anonymous reports. However, I will note that there are very clear federal and state regulations governing respirable dust levels in mines and the safety measures that are required to reduce employee exposure to dust. All American mines are required to follow those regulations.”
A New Era in Safety?
Many of the largest coal seams were long ago depleted, leaving only smaller, narrower seams for modern-day miners. There is still plenty of coal there, says Lilly, but to make room for the large machinery needed to extract it requires blasting through not just coal but also the surrounding rock. A major component of that rock is silica, the major contributor to silicosis.30,31
Weissman and others believe the combination of silica and coal dusts is especially toxic and is helping drive the surge in new CWP cases and causing them to progress so much faster than in previous generations.31,32 “This dust is more toxic, and the miners are inhaling more of it,” Weissman says. Rather than straight CWP, he says, what seems to be developing is a mixed dust disease with the worst aspects of both CWP and silicosis. This idea is supported, he says, by a recent histopathologic analysis of lung samples obtained from coal miners with advanced cases of CWP.32
As for why the increase in CWP is most striking in central Appalachia, the content of the coal itself might play a role, says Andrea Harrington, a postdoctoral research scientist at New York University School of Medicine. The coal mined in this region has an unusually high concentration of pyrite, an iron compound commonly known as fool’s gold.33 The iron in pyrite is fairly chemically reactive, stripping electrons from water molecules and creating reactive oxygen species in the form of hydrogen peroxide, hydroxyl radicals, superoxide, and/or singlet oxygen.34
A 2005 study reported an association between the pyrite content of the coal in various mining regions and the rates of CWP documented there.35 Harrington’s work shows that pyrite in coal dust increases inflammation,36 which increases lung damage.37 “It’s a dose issue,” she says. “Your body can only handle so many particles before it gets overwhelmed.”
The inhalation of any dust is likely to cause issues, Harrington adds. However, adding a reactive metal to inhaled dust only exacerbates the problems.
Decreasing numbers of U.S. coal mines—a result of competition from natural gas and declining profits38—means that U.S. coal production also is going down, in 2013 falling below 1 billion short tons for the first time in 20 years.39 Pressure to increase productivity with fewer miners means increased mechanization, which results in smaller and thus more harmful dust particles than hand labor can produce. Coal miners have also been working longer hours—this means they not only are exposed for longer periods but also have less time between shifts to clear the dust from their lungs.29
The miners believe that, whatever the cause for the increase, stronger labor laws and dust protections will help keep their fellow miners from getting sick. Their desire came to pass in 2014, when the Mine Safety and Health Administration issued updated rules for dust exposure. Among provisions set to go into effect in 2016, the allowable overall dust level was tightened from 2.0 mg/m3 to 1.5 mg/m3, and mine operators are now required to continuously monitor dust levels and take immediate action if dust levels are high.40
The changes also call for CWP surveillance to be conducted not only by X ray, but also by lung function testing using spirometry. Robert Cohen, a professor of pulmonary medicine at Northwestern University, says this can catch damage to the airways as well as scars on the lung caused by coal mine dust exposure.
Popovich says the mining industry believes more can and must be done to protect miners from exposure. “The industry offered concrete suggestions to the Mine Safety and Health Administration during the agency’s rule-making proceeding on a new dust standard,” he says, specifically calling for mandatory participation of all coal miners in the NIOSH surveillance program and adoption of a hierarchy of progressively more protective controls to reduce miners’ exposure to respirable dust.41 Popovich says these suggestions were not adopted by the agency.
It’s too soon to say whether the measures that were adopted will actually cause CWP numbers to drop, but researchers hope they will. “A disease that disables around ten percent of workers would be unacceptable in any other environment,” Blackley says. “They shouldn’t have to be exposed to this risk.”
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It is widely recognized that the hazard and dose response portions of chemical risk assessments are being transformed by the availability of Adverse Outcome Pathways (AOPs) and in vitro and in silico data on biological activity. This transformation is also changing the exposure assessment portion of the process. Exposure assessment supports the characterization of risk by estimating the doses received by individuals and converting the doses into dose metrics defined by dosing regimes from in vivo studies (lifetime average daily doses in mg/kg/d). In contrast, the dose metrics in in vitro assays are concentrations in test solutions over short periods of time (hours or days). In addition, an AOP begins with a molecular initiating event (MIE), which is also an short-term event (e.g., binding to a receptor). As a result, exposure assessment must now characterize the time course of concentrations of chemicals, or metabolites, at the site of the MIE that occur as a result of one or more short-term exposure events. These concentrations are determined by linking longitudinal models of intake doses to pharmacokinetic models of concentrations of a chemical, or its metabolites. Such approach will require improvements in the Agency’s ability to model longitudinal exposures and produce pharmacokinetic models of internal concentrations of chemicals, and their relevant metabolites, for large numbers of substances.
Exposure error in ambient air pollution epidemiologic studies may introduce bias and/or attenuation of the health risk estimate, reduce statistical significance, and lower statistical power. Alternative exposure metrics are increasingly being used in place of central-site measurements, with the intent of reducing exposure error. Dependent on the study design, health outcome, and pollutant of interest, these metrics may provide a means of reducing error (leading to less bias and uncertainty in health risk estimates) if they capture variability in exposure which is not represented when central-site measurements are used. We examine the current evidence for answering the question of when the choice of exposure metric matters and why, focusing on studies which examined multiple exposure metrics in the same epidemiologic study. We conclude that for time-series and case-crossover studies, central-site measurements may be sufficient, especially for homogeneous pollutants, and in cohort and panel studies, approaches that increase spatial resolution of the exposure metrics do impact the health effect estimates. We note that while the current literature is widely dispersed across exposure metrics and health outcomes, the largest collective, common body of literature is focused on birth/pregnancy outcomes and traffic-related pollution. Also additional discussion and agreement is needed on how to classify metrics as “different” and “better.” Primary recommendations are to provide context for the reasons behind selection of exposure metrics and to encourage collaboration between exposure scientists and epidemiologists when designing and implementing a study, as results can have important implications for the development of policies and regulations.
Wendee Nicole has written for Discover, Scientific American, and other publications.
Citation: Nicole W. 2016. Weeding out risk factors? Study reports no association between prenatal air pollution and autism. Environ Health Perspect 124:A23; http://dx.doi.org/10.1289/ehp.124-A23
Published: 1 January 2016
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Related EHP Article
Air Pollution Exposure during Pregnancy and Childhood Autistic Traits in Four European Population-Based Cohort Studies: The ESCAPE Project
In utero exposures to certain toxic constituents of traffic-related air pollution have been linked to neurological impairments. Recent studies have addressed whether exposures to such air toxicants might be environmental risk factors for autism spectrum disorders (ASDs)—developmental disabilities that can involve rigid, repetitive behaviors and impairments in communication and social interactions. Although several past studies reported associations between ASDs and certain air pollutants, a new analysis of four prospective cohorts published in this issue of EHP appears to contradict those findings, reporting no such associations.1
Working as part of the European Study of Cohorts for Air Pollution Effects (ESCAPE) project,2 the researchers analyzed data from four different prospective cohorts investigating ASDs in relation to air pollution. These studies assessed autistic traits, but not formal diagnoses of an ASD, in more than 8,000 children in the general population. The presence of autistic traits had been assessed using validated screening tests, which varied in the included studies. The authors of the current study used land-use regression models to estimate mothers’ at-home exposures to nitrogen oxides (NOx) and various sizes of particulate matter (PM) during pregnancy.1
Although several earlier studies reported a higher prevalence of autism in children exposed prenatally to traffic-related air pollutants, a new analysis of four prospective cohorts finds no such association.
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Depending on the study, 0.7–3.6% of these children—mostly boys—showed autistic traits in the clinical range, and 3.2–12.3% showed traits in the clinical/borderline range. In the final analysis, no associations were found between presence of autistic traits and prenatal exposure to any of the air pollutants.1
“Almost all previous studies carried out mainly in the United States found an association between air pollution and ASDs,” says lead author Mònica Guxens, an assistant research professor at the Centre for Research in Environmental Epidemiology in Barcelona. “I do not think that ASDs are different in Europe than in the U.S., but the best way to check what is going on here is to try to replicate the U.S. studies in Europe following a similar study design.”
Bing-Fang Hwang, a professor of environmental and occupational epidemiology at China Medical University, points out that in three of the studies parents assessed their children’s traits, while psychologists assessed traits in the fourth. “I do not think it’s appropriate to combine all results through meta-analysis without considering the heterogeneity of different diagnoses from parents and a psychologist,” he says. “It may cause bias in estimation of combined odds ratio. The results should be interpreted cautiously.”
The authors acknowledge this and other limitations in their paper. However, the consistent null findings across cohorts suggest their results are not spurious and must be investigated further.1
Raanan Raz, an epidemiologist at the Hebrew University of Jerusalem-Hadassah, says the study is important because it examines the issue of air pollution and autism in a new approach—looking at autistic traits in prospective cohorts of children enrolled at birth. He says, “The researchers interpreted [results] with appropriate caution, stating the possible explanations in their discussion.” Among those possible explanations, the authors hypothesize that cohorts of children like the ones in their study would have a vanishingly small proportion of the extreme autism phenotypes that appear in case–control studies.1
1. Guxens M, et al. Air pollution exposure during pregnancy and childhood autistic traits in four European population-based cohort studies: the ESCAPE Project. Environ Health Perspect 124(1):133–140 (2015), doi: 10.1289/ehp.1408483.
2. ESCAPE. European Study of Cohorts for Air Pollution Effects (ESCAPE) [website]. Utrecht, The Netherlands:European Study of Cohorts for Air Pollution Effects, Seventh Programme, European Union (updated 4 April 2014). Available: http://www.escapeproject.eu [accessed 7 December 2015].
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