Thomas F. Bateson

Children's Response to Air Pollutants

It is important to focus on children with respect to air pollution because (1) their lungs are not completely developed, (2) they can have greater exposures than adults, and (3) those exposures can deliver higher doses of different composition that may remain in the lung for greater duration. The undeveloped lung is more vulnerable to assault and less able to fully repair itself when injury disrupts morphogenesis. Children spend more time outside, where concentrations of combustion-generated air pollution are generally higher. Children have higher baseline ventilation rates and are more physically active than adults, thus exposing their lungs to more air pollution. Nasal breathing in adults reduces some pollution concentrations, but children are more typically mouth-breathers—suggesting that the composition of the exposure mixture at the alveolar level may be different. Finally, higher ventilation rates and mouth-breathing may pull air pollutants deeper into childrens lungs, thereby making clearance slower and more difficult. Children also have immature immune systems, which plays a significant role in asthma. The observed consequences of early life exposure to adverse levels of air pollutants include diminished lung function and increased susceptibility to acute respiratory illness and asthma. Exposure to diesel exhaust, in particular, is an area of concern for multiple endpoints, and deserves further research.

Increased Risk of Cancer Mortality Associated with Cadmium Exposures in Older Americans with Low Zinc Intake

Cadmium (Cd) exposure has been associated with increased cancer risk, and zinc (Zn) appears to reduce that risk. However, little is known about the combined influence of Cd and Zn on cancer risk. The aim of this study was to examine relationships between Cd exposure, Zn intake, and cancer mortality risks. The analyses used 5204 subjects aged 50 yr or older from the Third National Health and Nutrition Examination Survey (NHANES III, 1988–1994) and the mortality follow-up through December 31, 2006. Cox proportional hazards models were used to test associations. In total, 569 cancer deaths were recorded during an average follow-up of 12.4 yr, including 155 from lung, 61 from prostate, and 26 from breast cancer. A positive association between Cd and cancer mortality risk was identified for both genders. Despite limited cause-specific deaths, the increased risk associated with Cd was significant for lung cancer in men. All-cause cancer mortality risk was significantly elevated among women with Zn intakes below the recommended dietary allowance (RDA) compared with women who met the RDA. The effect of low dietary Zn was not observed in men. Similar trends for prostate and breast cancer deaths were not significant. There was a significant inverse association between cancer deaths and the Zn-to-Cd ratio for both genders. Cd exposure is an important independent risk factor of cancer mortality in older Americans and the risk appears exaggerated in those with inadequate dietary Zn. Additional studies are required to elucidate the mechanism(s) by which Zn participates in the carcinogenic influence of Cd.

A Reexamination of the PPAR-α Activation Mode of Action as a Basis for Assessing Human Cancer Risks of Environmental Contaminants

Background Diverse environmental contaminants, including the plasticizer di(2-ethylhexyl)phthalate (DEHP), are hepatocarcinogenic peroxisome proliferators in rodents. Peroxisome proliferator–activated receptor-α (PPAR-α) activation and its sequelae have been proposed to constitute a mode of action (MOA) for hepatocarcinogenesis by such agents as a sole causative factor. Further, based on a hypothesized lower sensitivity of humans to this MOA, prior reviews have concluded that rodent hepatocarcinogenesis by PPAR-α agonists is irrelevant to human carcinogenic risk. Data synthesis Herein, we review recent studies that experimentally challenge the PPAR-α activation MOA hypothesis, providing evidence that DEHP is hepatocarcinogenic in PPAR-α–null mice and that the MOA but not hepatocarcinogenesis is evoked by PPAR-α activation in a transgenic mouse model. We further examine whether relative potency for PPAR-α activation or other steps in the MOA correlates with tumorigenic potency. In addition, for most PPAR-α agonists of environmental concern, available data are insufficient to characterize relative human sensitivity to this rodent MOA or to induction of hepatocarcinogenesis. Conclusions Our review and analyses raise questions about the hypothesized PPAR-α activation MOA as a sole explanation for rodent hepatocarcinogenesis by PPAR-α agonists and therefore its utility as a primary basis for assessing human carcinogenic risk from the diverse compounds that activate PPAR-α. These findings have broad implications for how MOA hypotheses are developed, tested, and applied in human health risk assessment. We discuss alternatives to the current approaches to these key aspects of mechanistic data evaluation.

Panel discussion review: session three — issues involved in interpretation of epidemiologic analyses — statistical modeling

The Clean Air Act mandates that the US Environmental Protection Agency (EPA) develop National Ambient Air Quality Standards for criteria air pollutants and conduct periodic reviews of the standards based on new scientific evidence. In recent reviews, evidence from epidemiologic studies has played a key role. Epidemiologic studies often provide evidence for effects of several air pollutants. Determining whether there are independent effects of the separate pollutants is a challenge. Among the many issues confronting the interpretation of epidemiologic studies of multi-pollutant exposures and health effects are those specifically related to statistical modeling. The EPA convened a workshop on 13 and 14 December 2006 in Chapel Hill, North Carolina, USA, to discuss these and other issues; Session Three of the workshop was devoted specifically to statistical modeling. Prominent statistical modeling issues in epidemiologic studies of air pollution include (1) measurement error across the co-pollutants; (2) correlation and multi-collinearity among the co-pollutants; (3) the timing of the concentration–response function; (4) confounding; and (5) spatial analyses.The views expressed in this paper are those of the authors and do not necessarily reflect the views of policies of the US Environmental Protection Agency.

Effects of Exposure to 0.06 ppm Ozone on FEV1 in Humans: A Secondary Analysis of Existing Data

Background Ozone is a potent photochemical oxidant that produces transient, reversible decrements in the lung function of acutely exposed individuals. A recent study provided previously unavailable clinical data for 30 healthy young adults exposed to O3 at 0.06 ppm. That study showed significant effects of 0.08 ppm on lung function, confirming the findings of others. However, exposure to 0.06 ppm O3 was not reported to significantly affect lung function. Objectives We conducted this analysis to reevaluate the existing lung function data of the volunteers previously exposed to 0.06 ppm O3. Methods We obtained pre- and postexposure data on forced expiratory volume in 1 sec (FEV1) for all subjects who were previously exposed for 6.6 hr to filtered air or to 0.06 ppm or 0.08 ppm O3. We used standard statistical methods appropriate for paired comparisons to reanalyze FEV1 responses after exposure to 0.06 ppm O3 relative to filtered air. Results Controlling for filtered air responses, 24 of the 30 subjects experienced an O3-induced decrement in FEV1. On average, 0.06 ppm O3 exposure caused a 2.85% reduction in FEV1 (p < 0.002), which was consistent with the predicted FEV1 response from existing models. Although the average response was small, two subjects had > 10% FEV1 decrements. Conclusions Exposure to 0.06 ppm O3 causes a biologically small but highly statistically significant decrease in mean FEV1 responses of young healthy adults.

Human exposure to carbon-based fibrous nanomaterials: A review

In an emerging field of nanotechnologies, assessment of exposure to carbon nanotubes (CNT) and carbon nanofibers (CNF) is an integral component of occupational and environmental epidemiology, risk assessment and management, as well as regulatory actions. The current state of knowledge on exposure to carbon-based fibrous nanomaterials among workers, consumers and general population was studied in frame of the International Agency for Research on Cancer (IARC) Monographs-Volume 111 Some Nanomaterials and Some Fibres. Completeness and reliability of available exposure data for use in epidemiology and risk assessment were assessed. Occupational exposure to CNT/CNF may be of concern at all stages of the material life-cycle from research through manufacture to use and disposal. Consumer and environmental exposures are only estimated by modeled data. The available information of the final steps of the life-cycle of these materials remains incomplete so far regarding amounts of handled materials and levels of exposure. The quality and amount of information available on the uses and applications of CNT/CNF should be improved to enable quantitative assessment of human exposure to these materials. For that, coordinated effort in producing surveys and exposure inventories based on harmonized strategy of material test, exposure measurement and reporting results is strongly encouraged.

Regression Calibration for Classical Exposure Measurement Error in Environmental Epidemiology Studies Using Multiple Local Surrogate Exposures

Environmental epidemiologic studies are often hierarchical in nature if they estimate individuals personal exposures using ambient metrics. Local samples are indirect surrogate measures of true local pollutant concentrations which estimate true personal exposures. These ambient metrics include classical-type nondifferential measurement error. The authors simulated subjects true exposures and their corresponding surrogate exposures as the mean of local samples and assessed the amount of bias attributable to classical and Berkson measurement error on odds ratios, assuming that the logit of risk depends on true individual-level exposure. The authors calibrated surrogate exposures using scalar transformation functions based on observed within- and between-locality variances and compared regression-calibrated results with naive results using surrogate exposures. The authors further assessed the performance of regression calibration in the presence of Berkson-type error. Following calibration, bias due to classical-type measurement error, resulting in as much as 50% attenuation in naive regression estimates, was eliminated. Berkson-type error appeared to attenuate logistic regression results less than 1%. This regression calibration method reduces effects of classical measurement error that are typical of epidemiologic studies using multiple local surrogate exposures as indirect surrogate exposures for unobserved individual exposures. Berkson-type error did not alter the performance of regression calibration. This regression calibration method does not require a supplemental validation study to compute an attenuation factor.

A sensitivity analysis of bias in relative risk estimates due to disinfection by-product exposure misclassification.

We conducted a sensitivity analysis of relative risk estimates using local area mean disinfection by-product exposures. We used Monte Carlo simulations to generate data representing 100 towns, each with 100 births (n=10,000). Each town was assigned a mean total trihalomethane (TTHM) exposure value (mean=45, SD=28) based on a variable number of sampling locations (range 2–10). True maternal TTHM exposure was randomly assigned from a lognormal distribution using that towns true mean value. We compared the effect of a 20u2009μg/l increase in TTHM exposure on the risk of small-for-gestational age infancy using the true maternal exposure compared to various weighting measures of the town mean exposures. The exposure metrics included: (1) unweighted town mean, (2) town mean weighted by the inverse variance of the town mean, (3) town mean weighted by the inverse standard deviation of the town mean, (4) town mean weighted by 1−(standard deviation of sites per town/mean across all towns), and (5) a randomly selected value from one of the sites within the town of residence. To estimate the magnitude of misclassification bias from using the town mean concentrations, we compared the true exposure odds ratios (1.00, 1.20, 1.50, and 2.00) to the mean exposure odds ratios from the five exposure scenarios. Misclassification bias from the use of unweighted town mean exposures ranged from 19 to 39%, increasing in proportion to the size of the true effect estimates. Weighted town mean TTHM exposures were less biased than the unweighted estimates of maternal exposure, with bias ranging from 0 to 23%. The weighted town mean analyses showed that attenuation of the true effect of DBP exposure was diminished when town mean concentrations with large variability were downweighted. We observed a trade-off between bias and precision in the weighted exposure analyses, with the least biased effects estimates having the widest confidence intervals. Effect attenuation due to intrasystem variability was most evident in absolute and relative terms for larger odds ratios.

Evaluating uncertainty to strengthen epidemiologic data for use in human health risk assessments.

Background: There is a recognized need to improve the application of epidemiologic data in human health risk assessment especially for understanding and characterizing risks from environmental and occupational exposures. Although there is uncertainty associated with the results of most epidemiologic studies, techniques exist to characterize uncertainty that can be applied to improve weight-of-evidence evaluations and risk characterization efforts. Methods: This report derives from a Health and Environmental Sciences Institute (HESI) workshop held in Research Triangle Park, North Carolina, to discuss the utility of using epidemiologic data in risk assessments, including the use of advanced analytic methods to address sources of uncertainty. Epidemiologists, toxicologists, and risk assessors from academia, government, and industry convened to discuss uncertainty, exposure assessment, and application of analytic methods to address these challenges. Synthesis: Several recommendations emerged to help improve the utility of epidemiologic data in risk assessment. For example, improved characterization of uncertainty is needed to allow risk assessors to quantitatively assess potential sources of bias. Data are needed to facilitate this quantitative analysis, and interdisciplinary approaches will help ensure that sufficient information is collected for a thorough uncertainty evaluation. Advanced analytic methods and tools such as directed acyclic graphs (DAGs) and Bayesian statistical techniques can provide important insights and support interpretation of epidemiologic data. Conclusions: The discussions and recommendations from this workshop demonstrate that there are practical steps that the scientific community can adopt to strengthen epidemiologic data for decision making. Citation: Burns CJ, Wright JM, Pierson JB, Bateson TF, Burstyn I, Goldstein DA, Klaunig JE, Luben TJ, Mihlan G, Ritter L, Schnatter AR, Symons JM, Yi KD. 2014. Evaluating uncertainty to strengthen epidemiologic data for use in human health risk assessments. Environ Health Perspect 122:1160–1165;u2002http://dx.doi.org/10.1289/ehp.1308062

A review of the genotoxicity of 1,2-dichloroethane (EDC).

1,2-Dichloroethane (EDC, CAS#107-06-2) is a high production volume halogenated aliphatic hydrocarbon that is used mainly in the manufacture of vinyl chloride. EDC has been found in ambient and residential air samples, as well as in groundwater, surface water and drinking water. EDC has been well-studied in a variety of genotoxicity assays, and appears to involve the metabolic activation of the parent compound. We critically evaluated the genotoxicity data of EDC and its metabolites as part of an evaluation of carcinogenic mechanisms of action of EDC. EDC is genotoxic in multiple test systems via multiple routes of exposure. EDC has been shown to induce DNA adduct formation, gene mutations and chromosomal aberrations in the presence of key activation enzymes (including CYP450s and/or GSTs) in laboratory animal and in vitro studies. EDC was negative for clastogenesis as measured by the micronucleus assay in mice. In general, an increased level of DNA damage is observed related to the GSH-dependent bioactivation of EDC. Increased chromosomal aberrations with increased CYP450 expression were suggestive of a role for the oxidative metabolites of EDC in inducing chromosomal damage. Taken together, these studies demonstrate that EDC exposure, in the presence of key enzymes (including CYP450s and/or GSTs), leads to DNA adduct formation, gene mutations and chromosomal aberrations.