Systematic review and meta-analysis of birth weight and perfluorohexane sulfonate exposures: examination of sample timing and study confidence.

We examined the association between mean birth weight (BW) differences and perfluorohexane sulfonate (PFHxS) exposure biomarkers.We fit a random effects model to estimate the overall pooled effect and for different strata based on biomarker sample timing and overall study confidence. We also conducted an analysis to examine the impact of a continuous measure of gestational age sample timing on the overall pooled effect.We detected a -7.9 g (95% CI -15.0 to -0.7; pQ=0.85; I2=0%) BW decrease per ln ng/mL PFHxS increase based on 27 studies. The 11 medium confidence studies (ß=-10.0 g; 95% CI -21.1 to 1.1) showed larger deficits than 12 high (ß=-6.8 g; 95% CI -16.3 to 2.8) and 4 low confidence studies (ß=-1.5 g; 95% CI -51.6 to 48.7). 10 studies with mid-pregnancy to late-pregnancy sampling periods showed smaller deficits (ß=-3.9 g; 95% CI -17.7 to 9.9) than 5 post-partum studies (ß=-28.3 g; 95% CI -69.3 to 12.7) and 12 early sampling studies (ß=-7.6 g; 95% CI -16.2 to 1.1). 6 of 12 studies with the earliest sampling timing showed results closer to the null.Overall, we detected a small but statistically significant BW deficit across 27 studies. We saw comparable BW deficit magnitudes in both the medium and high confidence studies as well as the early pregnancy group. Despite no definitive pattern by sample timing, larger deficits were seen in postpartum studies. We also saw results closer to the null for a subset of studies restricted to the earliest biomarker collection times. Serial pregnancy sampling, improved precision in gestational age estimates and more standardised reporting of sample variation and exposure units in future epidemiologic research may offer a greater understanding of the relationship between PFHxS on BW and any potential impact of pregnancy haemodynamics.

Comparative susceptibility of children and adults to neurological effects of inhaled manganese: A review of the published literature.

BACKGROUND: Manganese (Mn) is neurotoxic in adults and children. Current assessments are based on the more extensive adult epidemiological data, but the potential for greater childhood susceptibility remains a concern. To better understand potential lifestage-based variations, we compared susceptibilities to neurotoxicity in children and adults using Mn biomarker data. METHODS: We developed a literature search strategy based on a Population, Exposures, Comparators, and Outcomes statement focusing on inhalation exposures and neurological outcomes in humans. Screening was performed using DistillerSR. Hair biomarker studies were selected for evaluation because studies with air measurements were unavailable or considered inadequate for children. Studies were paired based on concordant Mn source, biomarker, and outcome. Comparisons were made based on reported dose-response slopes (children vs. adults). Study evaluation was conducted to understand the confidence in our comparisons. RESULTS: We identified five studies evaluating seven pairings of hair Mn and neurological outcomes (cognition and motor effects) in children and adults matched on sources of environmental Mn inhalation exposure. Two Brazilian studies of children and one of adults reported intelligent quotient (IQ) effects; effects in both comparisons were stronger in children (1.21 to 2.03-fold difference). In paired analyses of children and adults from the United States, children exhibited both stronger and weaker effects compared to adults (0.37 to 1.75-fold differences) on postural sway metrics. CONCLUSION: There is limited information on the comparative susceptibility of children and adults to inhaled Mn. We report that children may be 0.37 to 2.03 times as susceptible as adults to neurotoxic effects of Mn, thereby providing a quantitative estimate for some aspects of lifestage variation. Due to the limited number of paired studies available in the literature, this quantitative estimate should be interpreted with caution. Our analyses do not account for other sources of inter-individual variation. Additional studies of Mn-exposed children with direct air concentration measurements would improve the evidence base.

The effect of age on the relative risk of lung cancer mortality in a cohort of chromium production workers.

BACKGROUND: Hexavalent chromium has been found to increase the risk of lung cancer in occupational studies. It has been suggested that the relative risk of lung cancer may vary by age. METHODS: The cohort examined is the Baltimore cohort of chromium production workers. The effect of age on the lung cancer risk from hexavalent chromium exposure was examined using a conditional Poisson regression modeling approach of Richardson and Langholz (R&L) and Cox models with interaction terms of age and cumulative hexavalent chromium exposure. RESULTS: The inclusion of multiple age groups in the R&L approach suggests the existence of an age effect that is also supported by a Cox proportional hazard analysis. The hazard ratio in Cox models with age-cumulative exposure interaction terms was significantly elevated for the youngest age group and significantly decreased for the oldest age group. CONCLUSIONS: Our analyses are consistent with the observation that younger chromium production workers have a greater lung cancer risk than older workers.

A tool to assess risk of bias in non-randomized follow-up studies of exposure effects (ROBINS-E).

BACKGROUND: Observational epidemiologic studies provide critical data for the evaluation of the potential effects of environmental, occupational and behavioural exposures on human health. Systematic reviews of these studies play a key role in informing policy and practice. Systematic reviews should incorporate assessments of the risk of bias in results of the included studies. OBJECTIVE: To develop a new tool, Risk Of Bias In Non-randomized Studies - of Exposures (ROBINS-E) to assess risk of bias in estimates from cohort studies of the causal effect of an exposure on an outcome. METHODS AND RESULTS: ROBINS-E was developed by a large group of researchers from diverse research and public health disciplines through a series of working groups, in-person meetings and pilot testing phases. The tool aims to assess the risk of bias in a specific result (exposure effect estimate) from an individual observational study that examines the effect of an exposure on an outcome. A series of preliminary considerations informs the core ROBINS-E assessment, including details of the result being assessed and the causal effect being estimated. The assessment addresses bias within seven domains, through a series of 'signalling questions'. Domain-level judgements about risk of bias are derived from the answers to these questions, then combined to produce an overall risk of bias judgement for the result, together with judgements about the direction of bias. CONCLUSION: ROBINS-E provides a standardized framework for examining potential biases in results from cohort studies. Future work will produce variants of the tool for other epidemiologic study designs (e.g. case-control studies). We believe that ROBINS-E represents an important development in the integration of exposure assessment, evidence synthesis and causal inference.

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 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.

Gas emissions from biodegradable waste in United Kingdom landfills.

The aim of this research was to predict the effect that the biodegradable municipal waste (BMW) diversion targets in the European Union landfill directive (99/31/EC) would have on landfill gas emissions. This is important for continued mitigation of these emissions. Work was undertaken in three stages using the GasSim model (v1.03) developed by the Environment Agency (England and Wales). The first stage considered the contribution to gas emissions made by each biodegradable component of the waste stream. The second stage considered how gas emissions from a landfill accepting biodegradable wastes with reduced biodegradable content would be affected. The third stage looked at the contribution to gas emissions from real samples of biologically pretreated BMW. For the first two stages, data on the waste components were available in the model. For the third stage samples were obtained from four different biological treatment facilities and the required parameters determined experimentally. The results of stage 1 indicated that in the first 15 years of the landfill the putrescible fraction makes the most significant contribution, after which paper/card becomes the most significant. The second stage found that biodegradability must be reduced by at least 60% to achieve a reduction in overall methane generation. The third stage found that emissions from samples of biologically pretreated BMW would result in a significant reduction in gas emissions over untreated waste, particularly in the early stage of the landfill lifetime; however, low level emissions would continue to occur for the long term.

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.

Characterization of compost-like outputs from mechanical biological treatment of municipal solid waste.

Throughout the world, most municipal solid waste consists of biodegradable components. The most abundant biological component is cellulose, followed by hemicellulose and lignin. Recycling of these components is important for the carbon cycle. In an attempt to reduce the environmental impacts of biodegradable wastes, mechanical biological treatments (MBTs) are being used as a waste management process in many countries. MBT plants attempt to mechanically separate the biodegradable and nonbiodegradable components. The nonbiodegradable components are then sent for reprocessing or landfilled, whereas the biodegradable components are reduced in biological content through composting or anaerobic digestion, leaving a compost-like output (CLO). The further use of these partially degraded residues is uncertain, and in many cases it is likely that they will be landfilled. The implications of this for the future of landfill management are causing some concern because there is little evidence that the long-term emissions tail will be reduced. In this study, the CLOs from four different biological treatment processes were characterized for physical contamination through visual inspection and for biological content using a sequential digestion analysis. The results indicate that the composition of the incoming waste, dependent on the way the waste was collected/segregated, was the factor that influenced biological content most, with length of treatment process the second most important.

Methods for evaluating variability in human health dose-response characterization.

The Reference Dose (RfD) and Reference Concentration (RfC) are human health reference values (RfVs) representing exposure concentrations at or below which there is presumed to be little risk of adverse effects in the general human population. The 2009 National Research Council report Science and Decisions recommended redefining RfVs as "a risk-specific dose (for example, the dose associated with a 1 in 100,000 risk of a particular end point)." Distributions representing variability in human response to environmental contaminant exposures are critical for deriving risk-specific doses. Existing distributions estimating the extent of human toxicokinetic and toxicodynamic variability are based largely on controlled human exposure studies of pharmaceuticals. New data and methods have been developed that are designed to improve estimation of the quantitative variability in human response to environmental chemical exposures. Categories of research with potential to provide new database useful for developing updated human variability distributions include controlled human experiments, human epidemiology, animal models of genetic variability, in vitro estimates of toxicodynamic variability, and in vitro-based models of toxicokinetic variability. In vitro approaches, with further development including studies of different cell types and endpoints, and approaches to incorporate non-genetic sources of variability, appear to provide the greatest opportunity for substantial near-term advances.

Development of outcome-specific criteria for study evaluation in systematic reviews of epidemiology studies.

INTRODUCTION AND OBJECTIVE: Systematic review tools that provide guidance on evaluating epidemiology studies are receiving increasing attention and support because their application facilitates improved quality of the review, consistency across reviewers, and transparency for readers. The U.S. Environmental Protection Agency's Integrated Risk Information System (IRIS) Program has developed an approach for systematic review of evidence of health effects from chemical exposures that includes structured approaches for literature search and screening, study evaluation, data extraction, and evidence synthesis and integration. This approach recognizes the need for developing outcome-specific criteria for study evaluation. Because studies are assessed at the outcome level, a study could be considered high quality for one investigated outcome, and low quality for another, due to differences in the outcome measures, analytic strategies, how relevant a certain bias is to the outcome, and how the exposure measure relates to the outcome. The objective of this paper is to illustrate the need for outcome-specific criteria in study evaluation or risk of bias evaluation, describe the process we used to develop the criteria, and summarize the resulting criteria. METHODS: We used a process of expert consultation to develop several sets of outcome-specific criteria to guide study reviewers, improve consistency, and ensure consideration of critical issues specific to the outcomes. The criteria were developed using the following domains: outcome assessment, exposure measurement (specifically timing of exposure in relation to outcome; other exposure measurement issues would be addressed in exposure-specific criteria), participant selection, confounding, analysis, and sensitivity (the study's ability to detect a true effect or hazard). RESULTS: We discuss the application of this process to pregnancy-related outcomes (preterm birth, spontaneous abortion), other reproductive-related outcomes (male reproductive hormones, sperm parameters, time to pregnancy, pubertal development), chronic disease (diabetes, insulin resistance), and acute or episodic conditions (asthma, allergies), and provide examples of the criteria developed. For each outcome the most influential methodological considerations are highlighted including biological sample collection and quality control, sensitivity and specificity of ascertainment tools, optimal timing for recruitment into the study (e.g., preconception, specific trimesters), the etiologically relevant window for exposure assessments, and important potential confounders. CONCLUSIONS: Outcome-specific criteria are an important part of a systematic review and will facilitate study evaluations by epidemiologists with experience in evaluating studies using systematic review methods who may not have extensive discipline-specific experience in the outcomes being reviewed.

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 O(3) 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 O(3) 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 O(3). METHODS: We obtained pre- and postexposure data on forced expiratory volume in 1 sec (FEV(1)) for all subjects who were previously exposed for 6.6 hr to filtered air or to 0.06 ppm or 0.08 ppm O(3). We used standard statistical methods appropriate for paired comparisons to reanalyze FEV(1) responses after exposure to 0.06 ppm O(3) relative to filtered air. RESULTS: Controlling for filtered air responses, 24 of the 30 subjects experienced an O(3)-induced decrement in FEV(1). On average, 0.06 ppm O(3) exposure caused a 2.85% reduction in FEV(1) (p < 0.002), which was consistent with the predicted FEV(1) response from existing models. Although the average response was small, two subjects had > 10% FEV(1) decrements. CONCLUSIONS: Exposure to 0.06 ppm O(3) causes a biologically small but highly statistically significant decrease in mean FEV(1) responses of young healthy adults.

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 children's 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.

Epidemiology: a foundation of environmental decision making.

Many epidemiologic studies are designed so they can be drawn upon to provide scientific evidence for evaluating hazards of environmental exposures, conducting quantitative assessments of risk, and informing decisions designed to reduce or eliminate harmful exposures. However, experimental animal studies are often relied upon for environmental and public health policy making despite the expanding body of observational epidemiologic studies that could inform the relationship between actual, as opposed to controlled, exposures and health effects. This paper provides historical examples of how epidemiology has informed decisions at the U.S. Environmental Protection Agency, discusses some challenges with using epidemiology to inform decision making, and highlights advances in the field that may help address these challenges and further the use of epidemiologic studies moving forward.

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.

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 town's true mean value. We compared the effect of a 20 microg/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.

Influence of exposure assessment and parameterization on exposure response. Aspects of epidemiologic cohort analysis using the Libby Amphibole asbestos worker cohort.

Recent meta-analyses of occupational epidemiology studies identified two important exposure data quality factors in predicting summary effect measures for asbestos-associated lung cancer mortality risk: sufficiency of job history data and percent coverage of work history by measured exposures. The objective was to evaluate different exposure parameterizations suggested in the asbestos literature using the Libby, MT asbestos worker cohort and to evaluate influences of exposure measurement error caused by historically estimated exposure data on lung cancer risks. Focusing on workers hired after 1959, when job histories were well-known and occupational exposures were predominantly based on measured exposures (85% coverage), we found that cumulative exposure alone, and with allowance of exponential decay, fit lung cancer mortality data similarly. Residence-time-weighted metrics did not fit well. Compared with previous analyses based on the whole cohort of Libby workers hired after 1935, when job histories were less well-known and exposures less frequently measured (47% coverage), our analyses based on higher quality exposure data yielded an effect size as much as 3.6 times higher. Future occupational cohort studies should continue to refine retrospective exposure assessment methods, consider multiple exposure metrics, and explore new methods of maintaining statistical power while minimizing exposure measurement error.

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.