A systematic evidence map for the evaluation of noncancer health effects and exposures to polychlorinated biphenyl mixtures.

Assessing health outcomes associated with exposure to polychlorinated biphenyls (PCBs) is important given their persistent and ubiquitous nature. PCBs are classified as a Group 1 carcinogen, but the full range of potential noncancer health effects from exposure to PCBs has not been systematically summarized and evaluated. We used systematic review methods to identify and screen the literature using combined manual review and machine learning approaches. A protocol was developed that describes the literature search strategy and Populations, Exposures, Comparators, and Outcomes (PECO) criteria used to facilitate subsequent screening and categorization of literature into a systematic evidence map of PCB exposure and noncancer health endpoints across 15 organs/systems. A comprehensive literature search yielded 62,599 records. After electronic prioritization steps, 17,037 studies were manually screened at the title and abstract level. An additional 900 studies identified by experts or supplemental searches were also included. After full-text screening of 3889 references, 1586 studies met the PECO criteria. Relevant study details such as the endpoints assessed, exposure duration, and species were extracted into literature summary tables. This review compiles and organizes the human and mammalian studies from these tables into an evidence map for noncancer health endpoints and PCB mixture exposure to identify areas of robust research as well as areas of uncertainty that would benefit from future investigation. Summary data are available online as interactive visuals with downloadable metadata. Sufficient research is available to inform PCB hazard assessments for most organs/systems, but the amount of data to inform associations with specific endpoints differs. Furthermore, despite many years of research, sparse data exist for inhalation and dermal exposures, which are highly relevant human exposure routes. This evidence map provides a foundation for future systematic reviews and noncancer hazard assessments of PCB mixtures and for strategic planning of research to inform areas of greater uncertainty.

The Role of Temperature in Modifying the Risk of Ozone-Attributable Mortality under Future Changes in Climate: A Proof-of-Concept Analysis.

Air pollution risk assessments typically estimate ozone-attributable mortality counts using concentration-response (C-R) parameters from epidemiologic studies that treat temperature as a potential confounder. However, some recent epidemiologic studies have indicated that temperature can modify the relationship between short-term ozone exposure and mortality, which has potentially important implications when considering the impacts of climate change on public health. This proof-of-concept analysis quantifies counts of temperature-modified ozone-attributable mortality using temperature-stratified C-R parameters from a multicity study in which the pooled ozone-mortality effect coefficients change in concert with daily temperature. Meteorology downscaled from two global climate models is used with a photochemical transport model to simulate ozone concentrations over the 21st century using two emission inventories: one holding air pollutant emissions constant at 2011 levels and another accounting for reduced emissions through the year 2040. The late century climate models project increased summer season temperatures, which in turn yields larger total counts of ozone-attributable deaths in analyses using temperature-stratified C-R parameters compared to the traditional temperature confounder approach. This analysis reveals substantial heterogeneity in the magnitude and distribution of the temperature-stratified ozone-attributable mortality results, which is a function of regional variability in both the C-R relationship and the model-predicted temperature and ozone.

Quantitative Characterization of Uncertainty in the Concentration-Response Relationship between Long-Term PM2.5 Exposure and Mortality at Low Concentrations.

Extensive epidemiologic evidence supports a linear, no-threshold concentration-response (C-R) relationship between long-term exposure to fine particles (PM2.5) and mortality in the United States. While examinations of the C-R relationship are designed to assess the shape of the C-R curve, they do not provide the information needed to quantitatively characterize uncertainty at specific PM2.5 concentrations, which is often needed in the context of risk assessments and benefits analyses. We developed a novel approach, using information that is typically available in published epidemiologic studies, to quantitatively characterize uncertainty at different concentrations along the PM2.5 concentration distribution. Our approach utilizes the annual mean PM2.5 concentration and corresponding standard deviation from a published epidemiologic study to estimate the standard deviation of hypothetical PM2.5 concentration distributions defined at 0.1 µg/m3 increments. The hypothetical distributions are then used to derive adjusted uncertainty estimates in the reported effect estimate at low concentrations (i.e., concentrations lower than the annual mean observed in the study). We demonstrate the application of this method in six individual epidemiologic studies that examined the relationship between long-term PM2.5 exposure and mortality and were conducted in different geographic locations worldwide and at different PM2.5 concentrations. This new method allows for a more comprehensive quantitative evaluation of uncertainty in the shape of the C-R relationship between long-term PM2.5 exposure and mortality at concentrations below the mean annual concentrations observed in current studies.

The estimated change in the level and distribution of PM2.5-attributable health impacts in the United States: 2005-2014.

BACKGROUND: Photochemical modeling can predict the level and distribution of pollutant concentrations over time, but is resource-intensive. Partly for this reason, there are few studies exploring the multi-year trajectory of the historical change in fine particle (PM2.5) levels and associated health impacts in the U.S. OBJECTIVES: We used a unique dataset of Community Multi-Scale Air Quality (CMAQ) model simulations performed for a subset of years over a decade-long period fused with observations to estimate the change in ambient levels of PM2.5 across the contiguous U.S. We also quantified the change in PM2.5-attributable health risks and characterized the level of risk inequality over this period. METHODS: We estimated annual mean PM2.5 concentrations in 2005, 2011 and 2014. Using log-linear and logistic concentration-response coefficients we estimated changes in the numbers of deaths, hospital admissions and other morbidity outcomes. Calculating the Gini coefficient and Atkinson Index, we characterized the extent to which PM2.5 attributable risks were shared equally across the population or instead concentrated among certain subgroups. RESULTS: In 2005 the estimated fraction of deaths due to PM2.5 was 6.1%. This estimated value falls to 4.6% by 2014. Every portion of the contiguous U.S. experiences a decline in the risk of PM-related premature death over the 10-year period. As measured by the Gini coefficient and Atkinson index, the level of PM mortality risk is shared more equally in 2014 than in 2005 among all subgroups. CONCLUSIONS: Between 2005 and 2014, the level of PM2.5 concentrations fall, and the risk of premature death, declined and became more equitably distributed across the U.S.

A cross-disciplinary evaluation of evidence for multipollutant effects on cardiovascular disease.

BACKGROUND: The current single-pollutant approach to regulating ambient air pollutants is effective at protecting public health, but efficiencies may be gained by addressing issues in a multipollutant context since multiple pollutants often have common sources and individuals are exposed to more than one pollutant at a time. OBJECTIVE: We performed a cross-disciplinary review of the effects of multipollutant exposures on cardiovascular effects. METHODS: A broad literature search for references including at least two criteria air pollutants (particulate matter [PM], ozone [O3], oxides of nitrogen, sulfur oxides, carbon monoxide) was conducted. References were culled based on scientific discipline then searched for terms related to cardiovascular disease. Most multipollutant epidemiologic and experimental (i.e., controlled human exposure, animal toxicology) studies examined PM and O3 together. DISCUSSION: Epidemiologic and experimental studies provide some evidence for O3 concentration modifying the effect of PM, although PM did not modify O3 risk estimates. Experimental studies of combined exposure to PM and O3 provided evidence for additivity, synergism, and/or antagonism depending on the specific health endpoint. Evidence for other pollutant pairs was more limited. CONCLUSIONS: Overall, the evidence for multipollutant effects was often heterogeneous, and the limited number of studies inhibited making a conclusion about the nature of the relationship between pollutant combinations and cardiovascular disease.

Multiple biomarker models for improved risk estimation of specific cardiovascular diseases related to metabolic syndrome: a cross-sectional study.

BACKGROUND: Metabolic syndrome (MetS) is the co-occurrence of several conditions that increase risk of chronic disease and mortality. Multivariate models for calculating risk of MetS-related diseases based on combinations of biomarkers are promising for future risk estimation if based on large population samples. Given biomarkers' nonspecificity and commonality in predicting diseases, we hypothesized that unique combinations of the same clinical diagnostic criteria can be used in different multivariate models to develop more accurate individual and cumulative risk estimates for specific MetS-related diseases. METHODS: We utilized adult biomarker and cardiovascular disease (CVD) data from the National Health and Nutrition Examination Survey as part of a cross-sectional analysis. Serum C-reactive protein (CRP), glycohemoglobin, triglycerides, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, total cholesterol, fasting glucose, and apolipoprotein-B were modeled. CVDs included congestive heart failure, coronary heart disease, angina, myocardial infarction, and stroke. Decile analysis for disease prevalence in each biomarker group and multivariate logistic regression for estimation of odds ratios were employed to measure the joint association between multiple biomarkers and CVD diagnoses. RESULTS: Of the biomarkers considered, glycohemoglobin, triglycerides, and CRP were consistently associated with the CVD outcomes of interest in decile analysis and were selected for the final models. Associations were overestimated when using single-marker models in comparison with full models; individual odds ratios decreased an average of 16.4% from the single-biomarker models to the joint association models for CRP, 6.6% for triglycerides, and 1.4% for glycohemoglobin. However, joint associations were stronger than any single-marker estimate. Additionally, reduced models produced unique combinations of biomarkers for specific CVD outcomes. CONCLUSION: The reduced joint association modeling results suggest that unique combinations of biomarkers with their related measure of association can be used to produce more accurate cumulative risk estimates for each CVD. Additionally, our results indicate that the use of multiple biomarkers in a single multivariate model may provide increased accuracy of individual biomarker association estimates by controlling for statistical artifacts and spurious relationships due to co-biomarker confounding.

Quantifying Multipollutant Health Impacts Using the Environmental Benefits Mapping and Analysis Program-Community Edition (BenMAP-CE): A Case Study in Atlanta, Georgia.

BACKGROUND: Air pollution risk assessments do not generally quantify health impacts using multipollutant risk estimates, but instead use results from single-pollutant or copollutant models. Multipollutant epidemiological models account for pollutant interactions and joint effects but can be computationally complex and data intensive. Risk estimates from multipollutant studies are therefore challenging to implement in the quantification of health impacts. OBJECTIVES: Our objective was to conduct a case study using a developmental multipollutant version of the Environmental Benefits Mapping and Analysis Program-Community Edition (BenMAP-CE) to estimate the health impact associated with changes in multiple air pollutants using both a single and multipollutant approach. METHODS: BenMAP-CE was used to estimate the change in the number of pediatric asthma emergency department (ED) visits attributable to simulated changes in air pollution between 2011 and 2025 in Atlanta, Georgia, applying risk estimates from an epidemiological study that examined short-term single-pollutant and multipollutant (with and without first-order interactions) exposures. Analyses examined individual pollutants (i.e., ozone, fine particulate matter, carbon monoxide, nitrogen dioxide (NO2), sulfur dioxide, and particulate matter components) and combinations of these pollutants meant to represent shared properties or predefined sources (i.e., oxidant gases, secondary pollutants, traffic, power plant, and criteria pollutants). Comparisons were made between multipollutant health impact functions (HIF) and the sum of single-pollutant HIFs for the individual pollutants that constitute the respective pollutant groups. RESULTS: Photochemical modeling predicted large decreases in most of the examined pollutant concentrations between 2011 and 2025 based on sector specific (i.e., source-based) estimates of growth and anticipated controls. Estimated number of avoided asthma ED visits attributable to any given multipollutant group were generally higher when using results from models that included interaction terms in comparison with those that did not. We estimated the greatest number of avoided pediatric asthma ED visits for pollutant groups that include NO2 (i. e., criteria pollutants, oxidants, and traffic pollutants). In models that accounted for interaction, year-round estimates for pollutant groups that included NO2 ranged from 27.1 [95% confidence interval (CI): 1.6, 52.7; traffic pollutants] to 55.4 (95% CI: 41.8, 69.0; oxidants) avoided pediatric asthma ED visits. Year-round results using multipollutant risk estimates with interaction were comparable to the sum of the single-pollutant results corresponding to most multipollutant groups [e.g., 52.9 (95% CI: 43.6, 62.2) for oxidants] but were notably lower than the sum of the single-pollutant results for some pollutant groups [e.g., 77.5 (95% CI: 66.0, 89.0) for traffic pollutants]. DISCUSSION: Performing a multipollutant health impact assessment is technically feasible but computationally complex. It requires time, resources, and detailed input parameters not commonly reported in air pollution epidemiological studies. Results estimated using the sum of single-pollutant models are comparable to those quantified using a multipollutant model. Although limited to a single study and location, assessing the trade-offs between a multipollutant and single-pollutant approach is warranted. https://doi.org/10.1289/EHP12969.

The relationship between childhood blood lead levels below 5 µg/dL and childhood intelligence quotient (IQ): Protocol for a systematic review and meta-analysis.

BACKGROUND: The causal association between childhood lead (Pb) exposure and decrements in intelligence quotient (IQ) is well-established, and no safe blood lead level (BLL) in children has been identified. An international pooled analysis of seven prospective studies published by Lanphear et al. in 2005 quantified the relationship between childhood BLL and IQ. Further studies of Pb and IQ have been published more recently with mean BLLs generally lower than in the studies analyzed by Lanphear et al. In this article, we present the protocol for a systematic review to estimate an updated Pb-IQ relationship focusing on BLLs below 5 µg per deciliter (µg/dL). STUDY QUESTION: What is the quantitative relationship between childhood BLLs and IQ at ages 3-17 years at BLLs below 5 µg/dL? DATA SOURCES: A comprehensive search of the scientific literature will utilize citation mapping and key word searching. In the citation mapping approach, we will identify seed references that are relevant to our study question, and will then identify more recent references that have cited at least one of the seed references. The key word search will be conducted in the PubMed, Biosis Previews, Scopus, and Web of Science databases. We will also search electronic grey literature databases for conference proceedings, dissertations, and preprints. STUDY ELIGIBILITY CRITERIA, STUDY SCREENING AND DATA EXTRACTION: We will include studies that measured BLL in children at any age, assessed full-scale IQ of the same children (concurrent with or subsequent to BLL sample collection) at ages 3-17, and estimated a continuous quantitative relationship between BLL and IQ. We will consider only studies with a central tendency BLL < 10 µg/dL. The title and abstract of each record will be reviewed independently by two authors to determine whether the study in question satisfies the inclusion criteria. The full text of each article remaining after title-abstract screening will be reviewed independently by two authors to determine whether the study in question satisfies the inclusion criteria. Two authors will independently extract study characteristics and data from each included study. RISK OF BIAS ASSESSMENT: Studies meeting inclusion criteria will be evaluated for risk of bias (RoB) using the Navigation Guide method applied in a previous systematic review of neurodevelopmental effects (Lam et al., 2017), with adaptation to our study question. Each study will be independently evaluated by two review authors. DATA ANALYSIS AND SYNTHESIS: We intend to conduct a random-effects meta-analysis to summarize the effects of children's exposure to Pb on IQ scores. Additionally, we plan to perform sensitivity analyses using sub-group analyses and/or meta-regression techniques to assess the impact of study design and study population characteristics to examine potential heterogeneity of results across studies. We will assign a confidence level rating (high, moderate, low, or very low) to the effect estimate from the meta-analyses/meta-regressions.

Exposure to Perfluorinated Alkyl Substances and Health Outcomes in Children: A Systematic Review of the Epidemiologic Literature.

Perfluoroalkyl substances (PFAS), chemicals used to make products stain and stick resistant, have been linked to health effects in adults and adverse birth outcomes. A growing body of literature also addresses health effects in children exposed to PFAS. This review summarizes the epidemiologic evidence for relationships between prenatal and/or childhood exposure to PFAS and health outcomes in children as well as to provide a risk of bias analysis of the literature. A systematic review was performed by searching PubMed for studies on PFAS and child health outcomes. We identified 64 studies for inclusion and performed risk of bias analysis on those studies. We determined that risk of bias across studies was low to moderate. Six categories of health outcomes emerged. These were: immunity/infection/asthma, cardio-metabolic, neurodevelopmental/attention, thyroid, renal, and puberty onset. While there are a limited number of studies for any one particular health outcome, there is evidence for positive associations between PFAS and dyslipidemia, immunity (including vaccine response and asthma), renal function, and age at menarche. One finding of note is that while PFASs are mixtures of multiple compounds few studies examine them as such, therefore the role of these compounds as complex mixtures remains largely unknown.

Associations between Maternal Water Consumption and Birth Defects in the National Birth Defects Prevention Study (2000-2005).

BACKGROUND: Water and water-based beverages constitute a major part of daily fluid intake for pregnant women, yet few epidemiologic studies have investigated the role of water consumption on birth outcomes. METHODS: We used data from the National Birth Defects Prevention Study to conduct a case-control study investigating associations between maternal water consumption during pregnancy and birth defects (BD). We used interview data on water consumption during the first trimester of pregnancy in 14,454 cases (major BDs n ≥ 50) and 5,063 controls. Total water consumption was analyzed as a continuous variable and in quartiles. We evaluated the role of dietary quality and sugar sweetened beverage consumption. Logistic regression models were used to assess effects of water consumption on risk of BDs with adjustment for relevant covariates. RESULTS: Mean daily maternal water consumption among controls was 4.4 eight-ounce glasses. We observed decreases in estimated risk associated with increases in water consumption for several BDs, including neural tube defects (spina bifida), oral clefts (cleft lip), musculoskeletal defects (gastroschisis, limb deficiencies), and congenital heart defects (hypoplastic left heart syndrome, right-sided obstructions, pulmonary valve stenosis). Our results were generally unchanged when an indicator for overall dietary quality was included; however, there was evidence of effect measure modification by heavy consumption of sugar-sweetened beverages for some defects, but not all. CONCLUSION: These analyses suggest the importance of sufficient water consumption during early pregnancy, above and beyond it being a marker of higher diet quality. Additional analyses are warranted to understand the biological mechanism for this association. Birth Defects Research 109:193-202, 2017. © 2016 Wiley Periodicals, Inc.

Regulation of basement membrane-reactive B cells in BXSB, (NZBxNZW)F1, NZB, and MRL/lpr lupus mice.

Autoantibodies to diverse antigens escape regulation in systemic lupus erythematosus under the influence of a multitude of predisposing genes. To gain insight into the differential impact of diverse genetic backgrounds on tolerance mechanisms controlling autoantibody production in lupus, we established a single lupus-derived nephritis associated anti-basement membrane Ig transgene on each of four inbred murine lupus strains, including BXSB, (NZBxNZW)F1, NZB, and MRL/lpr, as approved by the Duke University and the Durham Veterans Affairs Medical Centers' Animal Care and Use Committees. In nonautoimmune C57BL/6 mice, B cells bearing this anti-laminin Ig transgene are stringently regulated by central deletion, editing, and anergy. Here, we show that tolerance is generally intact in unmanipulated Ig transgenic BXSB, (NZBxNZW)F1, and NZB mice, based on absence of serum transgenic anti-laminin autoantibodies and failure to recover spontaneous anti-laminin monoclonal antibodies. Four- to six-fold depletion of splenic B cells in transgenic mice of these strains, as well as in MRL/lpr transgenic mice, and reduced frequency of IgM+ bone marrow B cells suggest that central deletion is grossly intact. Nonetheless the 4 strains demonstrate distinct transgenic B cell phenotypes, including endotoxin-stimulated production of anti-laminin antibodies by B cells from transgenic NZB mice, and in vitro hyperproliferation of both endotoxin- and BCR-stimulated B cells from transgenic BXSB mice, which are shown to have an enrichment of CD21-high marginal zone cells. Rare anti-laminin transgenic B cells spontaneously escape tolerance in MRL/lpr mice. Further study of the mechanisms underlying these strain-specific B cell fates will provide insight into genetic modification of humoral autoimmunity in lupus.