J. Allen Davis

Introduction to benchmark dose methods and U.S. EPA's benchmark dose software (BMDS) version 2.1.1

Traditionally, the No-Observed-Adverse-Effect-Level (NOAEL) approach has been used to determine the point of departure (POD) from animal toxicology data for use in human health risk assessments. However, this approach is subject to substantial limitations that have been well defined, such as strict dependence on the dose selection, dose spacing, and sample size of the study from which the critical effect has been identified. Also, the NOAEL approach fails to take into consideration the shape of the dose-response curve and other related information. The benchmark dose (BMD) method, originally proposed as an alternative to the NOAEL methodology in the 1980s, addresses many of the limitations of the NOAEL method. It is less dependent on dose selection and spacing, and it takes into account the shape of the dose-response curve. In addition, the estimation of a BMD 95% lower bound confidence limit (BMDL) results in a POD that appropriately accounts for study quality (i.e., sample size). With the recent advent of user-friendly BMD software programs, including the U.S. Environmental Protection Agencys (U.S. EPA) Benchmark Dose Software (BMDS), BMD has become the method of choice for many health organizations world-wide. This paper discusses the BMD methods and corresponding software (i.e., BMDS version 2.1.1) that have been developed by the U.S. EPA, and includes a comparison with recently released European Food Safety Authority (EFSA) BMD guidance.

Associations Between Prenatal Exposure to Air Pollution, Small for Gestational Age, and Term Low Birthweight in a State-Wide Birth Cohort

A range of health effects, including adverse pregnancy outcomes, have been associated with exposure to ambient concentrations of particulate matter (PM) and ozone (O3). The objective of this study was to determine whether maternal exposure to fine particulate matter (PM2.5) and O3 during pregnancy is associated with the risk of term low birthweight and small for gestational age infants in both single and co-pollutant models. Term low birthweight and small for gestational age were determined using all birth certificates from North Carolina from 2003 to 2005. Ambient air concentrations of PM2.5 and O3 were predicted using a hierarchical Bayesian model of air pollution that combined modeled air pollution estimates from the EPA׳s Community Multi-Scale Air Quality (CMAQ) model with air monitor data measured by the EPA׳s Air Quality System. Binomial regression, adjusted for multiple potential confounders, was performed. In adjusted single-pollutant models for the third trimester, O3 concentration was positively associated with small for gestational age and term low birthweight births [risk ratios for an interquartile range increase in O3: 1.16 (95% CI 1.11, 1.22) for small for gestational age and 2.03 (95% CI 1.80, 2.30) for term low birthweight]; however, inverse or null associations were observed for PM2.5 [risk ratios for an interquartile range increase in PM2.5: 0.97 (95% CI 0.95, 0.99) for small for gestational age and 1.01 (95% CI 0.97, 1.06) for term low birthweight]. Findings were similar in co-pollutant models and linear models of birthweight. These results suggest that O3 concentrations in both urban and rural areas may be associated with an increased risk of term low birthweight and small for gestational age births.

Early prenatal exposure to air pollution and its associations with birth defects in a state-wide birth cohort from North Carolina

BACKGROUNDnFew studies have examined the potential relationship between air pollution and birth defects. The objective of this study was to investigate whether maternal exposure to particulate matter (PM2.5 ) and ozone (O3 ) during pregnancy is associated with birth defects among women living throughout North Carolina.nnnMETHODSnInformation on maternal and infant characteristics was obtained from North Carolina birth certificates and health service data (2003-2005) and linked with information on birth defects from the North Carolina Birth Defects Monitoring Program. The 24-hr PM2.5 and O3 concentrations were estimated using a hierarchical Bayesian model of air pollution generated by combining modeled air pollution predictions from the U.S. Environmental Protection Agencys Community Multi-Scale Air Quality model with air monitor data from the Environmental Protection Agencys Air Quality System. Maternal residence was geocoded and assigned pollutant concentrations averaged over weeks 3 to 8 of gestation. Binomial regression was performed and adjusted for potential confounders.nnnRESULTSnNo association was observed between either PM2.5 or O3 concentrations and most birth defects. Positive effect estimates were observed between air pollution and microtia/anotia and lower limb deficiency defects, but the 95% confidence intervals were wide and included the null.nnnCONCLUSIONnOverall, this study suggested a possible relationship between air pollution concentration during early pregnancy and certain birth defects (e.g., microtia/anotia, lower limb deficiency defects), although this study did not have the power to detect such an association. The risk for most birth defects does not appear to be affected by ambient air pollution.

An Ecologic Analysis of County-Level PM2.5 Concentrations and Lung Cancer Incidence and Mortality

Few studies have explored the relationship between PM2.5 and lung cancer incidence. Although results are mixed, some studies have demonstrated a positive relationship between PM2.5 and lung cancer mortality. Using an ecologic study design, we examined the county-level associations between PM2.5 concentrations (2002–2005) and lung cancer incidence and mortality in North Carolina (2002–2006). Positive trends were observed between PM2.5 concentrations and lung cancer incidence and mortality; however, the R2 for both were <0.10. The slopes for the relationship between PM2.5 and lung cancer incidence and mortality were 1.26 (95% CI 0.31, 2.21, p-value 0.01) and 0.73 (95% CI 0.09, 1.36, p-value 0.03) per 1 μg/m3 PM2.5, respectively. These associations were slightly strengthened with the inclusion of variables representing socioeconomic status and smoking. Although variability is high, thus reflecting the importance of tobacco smoking and other etiologic agents that influence lung cancer incidence and mortality besides PM2.5, a positive trend is observed between PM2.5 and lung cancer incidence and mortality. This suggests the possibility of an association between PM2.5 concentrations and lung cancer incidence and mortality.

A multi-level model of blood lead as a function of air lead

National and local declines in lead (Pb) in blood (PbB) over the past several years coincide with the decline in ambient air Pb (PbA) concentrations. The objective of this work is to evaluate how the relationship between PbB levels and PbA levels has changed following the phase out of leaded gasoline and tightened controls on industrial Pb emissions over the past 30 years among a national population sample. Participant-level data from the National Health and Nutrition Examination Survey (NHANES) were employed for two time periods (1988-1994 and 1999-2008), and the model was corrected for housing, demographic, socioeconomic, and other covariates present in NHANES. NHANES data for PbB and covariates were merged with PbA data from the U.S. Environmental Protection Agency. Linear mixed effects models (LMEs) were run to assess the relationship of PbB with PbA; sample weights were omitted, given biases encountered with the use of sample weights in LMEs. The 1988-1994 age-stratified results found that ln(PbB) was statistically significantly associated with ln(PbA) for all age groups. The consistent influence of PbA on PbB across age groups for the years 1988-1994 suggests a ubiquitous exposure unrelated to age of the sample population. The comparison of effect estimates for ln(PbA) shows a statistically significant effect estimate and ANOVA results for ln(PbB) for the 6- to 11-year and 12- to 19-year age groups during 1999-2008. The more recent finding suggests that PbA has less consistent influence on PbB compared with other factors.

Contribution of Particle-Size-Fractionated Airborne Lead to Blood Lead during the National Health and Nutrition Examination Survey, 1999–2008

The objective of this work is to examine associations between blood lead (PbB) and air lead (PbA) in particulate matter measured at different size cuts by use of PbB concentrations from the National Health and Nutrition Examination Survey and PbA concentrations from the U.S. Environmental Protection Agency for 1999-2008. Three size fractions of particle-bound PbA (TSP, PM10, and PM2.5) data with different averaging times (current and past 90-day average) were utilized. A multilevel linear mixed effect model was used to characterize the PbB-PbA relationship. At 0.15 μg/m(3), a unit decrease in PbA in PM10 was significantly associated with a decrease in PbB of 0.3-2.2 μg/dL across age groups and averaging times. For PbA in PM2.5 and TSP, slopes were generally positive but not significant. PbB levels were more sensitive to the change in PbA concentrations for children (1-5 and 6-11 years) and older adults (≥ 60 years) than teenagers (12-19 years) and adults (20-59 years). For the years following the phase-out of Pb in gasoline and a resulting upward shift in the PbA particle size distribution, PbA in PM10 was a statistically significant predictor of PbB. The results also suggest that age could affect the PbB-PbA association, with children having higher sensitivity than adults.

Regional variations in particulate matter composition and the ability of monitoring data to represent population exposures.

Epidemiologic studies have demonstrated that relative risks for mortality associated with ambient particulate matter (PM) concentrations vary with location in the U.S. with larger associations in both magnitude and strength observed in the East compared to the West. Two factors potentially contributing to the regional heterogeneity in PM-mortality associations observed are regional variations in PM composition and the ability of a single PM concentration estimate to represent the community-average exposure for an entire study area, which may lead to regional differences in exposure error. Variations in PM composition and the proportion of the population living in proximity to ambient monitors, an indicator of potential exposure error, are examined for the 20 most populated and 10 mid-size study areas included in the National Morbidity, Mortality and Air Pollution Study (NMMAPS). Clear differences in PM and in the proportion of the population living in proximity to ambient monitors are found for some of these cities. Differences in these exposure parameters may be interpreted more reasonably in terms of north-south differences compared to east-west differences, and may need to be considered when conducting future epidemiologic studies that aim to examine the factors that influence the regional variability in PM-mortality associations.

An exploratory analysis of the relationship between ambient ozone and particulate matter concentrations during early pregnancy and selected birth defects in Texas

We performed an exploratory analysis of ozone (O3) and fine particulate matter (PM2.5) concentrations during early pregnancy and multiple types of birth defects. Data on births were obtained from the Texas Birth Defects Registry (TBDR) and the National Birth Defects Prevention Study (NBDPS) in Texas. Air pollution concentrations were previously determined by combining modeled air pollution concentrations with air monitoring data. The analysis generated hypotheses for future, confirmatory studies; although many of the observed associations were null. The hypotheses are provided by an observed association between O3 and craniosynostosis and inverse associations between PM2.5 and septal and obstructive heart defects in the TBDR. Associations with PM2.5 for septal heart defects and ventricular outflow tract obstructions were null using the NBDPS. Both the TBDR and the NBPDS had inverse associations between O3 and septal heart defects. Further research to confirm the observed associations is warranted.

Cross-species coherence in effects and modes of action in support of causality determinations in the U.S. Environmental Protection Agency’s Integrated Science Assessment for Lead

The peer-reviewed literature on the health and ecological effects of lead (Pb) indicates common effects and underlying modes of action across multiple organisms for several endpoints. Based on such observations, the United States (U.S.) Environmental Protection Agency (EPA) applied a cross-species approach in the 2013 Integrated Science Assessment (ISA) for Lead for evaluating the causality of relationships between Pb exposure and specific endpoints that are shared by humans, laboratory animals, and ecological receptors (i.e., hematological effects, reproductive and developmental effects, and nervous system effects). Other effects of Pb (i.e., cardiovascular, renal, and inflammatory responses) are less commonly assessed in aquatic and terrestrial wildlife limiting the application of cross-species comparisons. Determinations of causality in ISAs are guided by a framework for classifying the weight of evidence across scientific disciplines and across related effects by considering aspects such as biological plausibility and coherence. As illustrated for effects of Pb where evidence across species exists, the integration of coherent effects and common underlying modes of action can serve as a means to substantiate conclusions regarding the causal nature of the health and ecological effects of environmental toxicants.

Can Data Science Inform Environmental Justice and Community Risk Screening for Type 2 Diabetes

Background Having the ability to scan the entire country for potential “hotspots” with increased risk of developing chronic diseases due to various environmental, demographic, and genetic susceptibility factors may inform risk management decisions and enable better environmental public health policies. Objectives Develop an approach for community-level risk screening focused on identifying potential genetic susceptibility hotpots. Methods Our approach combines analyses of phenotype-genotype data, genetic prevalence of single nucleotide polymorphisms, and census/geographic information to estimate census tract-level population attributable risks among various ethnicities and total population for the state of California. Results We estimate that the rs13266634 single nucleotide polymorphism, a type 2 diabetes susceptibility genotype, has a genetic prevalence of 56.3%, 47.4% and 37.0% in Mexican Mestizo, Caucasian, and Asian populations. Looking at the top quintile for total population attributable risk, 16 California counties have greater than 25% of their population living in hotspots of genetic susceptibility for developing type 2 diabetes due to this single genotypic susceptibility factor. Conclusions This study identified counties in California where large portions of the population may bear additional type 2 diabetes risk due to increased genetic prevalence of a susceptibility genotype. This type of screening can easily be extended to include information on environmental contaminants of interest and other related diseases, and potentially enables the rapid identification of potential environmental justice communities. Other potential uses of this approach include problem formulation in support of risk assessments, land use planning, and prioritization of site cleanup and remediation actions.