Sources, pathways and concentrations of potentially toxic trace metals in home environments.

Despite ongoing concerns about trace metal and metalloid (trace metals) exposure risks from indoor dust, there has been limited research examining their sources and relationship to outdoor soils. Here we determine the concentrations and sources for potentially toxic trace metals arsenic (As), chromium (Cr), copper (Cu), manganese (Mn), lead (Pb) and zinc (Zn) and their pathways into homes in Sydney, Australia, using home-matched indoor dust (n = 166), garden soil (n = 166), and road dust samples (n = 51). All trace metals were more elevated indoors versus their matched garden soil counterparts. Indoor Cu and Zn dust concentrations were significantly more enriched than outdoor dusts and soils, indicating indoor sources were more relevant for these elements. By contrast, even though Pb was elevated in indoor dust, garden soil concentrations were correspondingly high, indicating that it remains an important source and pathway for indoor contamination. Elevated concentrations of As, Pb and Zn in garden soil and indoor dust were associated with home age (>50 years), construction materials, recent renovations and deteriorating interior paint. Significant correlations (p < 0.05) between road dust and garden soil Cu concentrations, and those of As and Zn in soil and indoor dust, and Pb across all three media suggest common sources. Scanning electron microscopy (SEM) analysis of indoor dust samples (n = 6) showed that 57% of particles were derived from outdoor sources. Lead isotopic compositions of soil (n = 21) and indoor dust (n = 21) were moderately correlated, confirming the relevance of outdoor contaminants to indoor environments. This study illustrates the source, relationship and fate of trace metals between outdoor and indoor environments. The findings provide insight into understanding and responding to potentially toxic trace metal exposures in the home environment.

International Analysis of Sources and Human Health Risk Associated with Trace Metal Contaminants in Residential Indoor Dust.

People spend increasing amounts of time at home, yet the indoor home environment remains understudied in terms of potential exposure to toxic trace metals. We evaluated trace metal (and metalloid) concentrations (As, Cu, Cr, Mn, Ni, Pb, and Zn) and health risks in indoor dust from homes from 35 countries, along with a suite of potentially contributory residential characteristics. The objective was to determine trace metal source inputs and home environment conditions associated with increasing exposure risk across a range of international communities. For all countries, enrichments compared to global crustal values were Zn > Pb > Cu > As > Cr > Ni; with the greatest health risk from Cr, followed by As > Pb > Mn > Cu > Ni > Zn. Three main indoor dust sources were identified, with a Pb-Zn-As factor related to legacy Pb sources, a Zn-Cu factor reflecting building materials, and a Mn factor indicative of natural soil sources. Increasing home age was associated with greater Pb and As concentrations (5.0 and 0.48 mg/kg per year of home age, respectively), as were peeling paint and garden access. Therefore, these factors form important considerations for the development of evidence-based management strategies to reduce potential risks posed by indoor house dust. Recent findings indicate neurocognitive effects from low concentrations of metal exposures; hence, an understanding of the home exposome is vital.

Novel Application of Machine Learning Algorithms and Model-Agnostic Methods to Identify Factors Influencing Childhood Blood Lead Levels.

Blood lead (Pb) poisoning remains a global concern, particularly for children in their early developmental years. Broken Hill is Australia's oldest operating silver-zinc-lead mine. In this study, we utilized recent advances in machine learning to assess multiple algorithms and identify the most optimal model for predicting childhood blood Pb levels (BLL) using Broken Hill children's (<5 years of age) data (n = 23,749) from 1991 to 2015, combined with demographic, socio-economic, and environmental influencing factors. We applied model-agnostic methods to interpret the most optimal model, investigating different environmental and human factors influencing childhood BLL. Algorithm assessment showed that stacked ensemble, a method for automatically and optimally combining multiple prediction algorithms, enhanced predictive performance by 1.1% with respect to mean absolute error (p < 0.01) and 2.6% for root-mean-squared error (p < 0.01) compared to the best performing constituent algorithm (random forest). By interpreting the model, the following information was acquired: children had higher BLL if they resided within 1.0 km to the central mine area or 1.37 km to the railroad; year of testing had the greatest interactive strength with all other factors; BLL increased faster in Aboriginal than in non-Aboriginal children at 9-10 and 12-18 months of age. This "stacked ensemble + model-agnostic interpretation" framework achieved both prediction accuracy and model interpretability, identifying previously unconnected variables associated with elevated childhood BLL, offering a marked advantage over previous works. Thus, this approach has a clear value and potential for application to other environmental health issues.

The use of a physiologically-based extraction test to assess relationships between bioaccessible metals in urban soil and neurodevelopmental conditions in children.

Intellectual disability (ID) and cerebral palsy (CP) are serious neurodevelopment conditions and low birth weight (LBW) is correlated with both ID and CP. The actual causes and mechanisms for each of these child outcomes are not well understood. In this study, the relationship between bioaccessible metal concentrations in urban soil and these child conditions were investigated. A physiologically based extraction test (PBET) mimicking gastric and intestinal processes was applied to measure the bio-accessibility of four metals (cadmium (Cd), chromium (Cr), nickel (Ni), and lead (Pb)) in urban soil, and a Bayesian Kriging method was used to estimate metal concentrations in geocoded maternal residential sites. The results showed that bioaccessible metal concentrations of Cd, Ni, and Pb in the intestinal phase were statistically significantly associated with the child outcomes. Lead and nickel were associated with ID, lead and cadmium was associated with LBW, and cadmium was associated with CP. The total concentrations and stomach concentrations were not correlated to significant effects in any of the analyses. For lead, an estimated threshold value was found that was statistically significant in predicting low birth weight. The change point test was statistically significant (p value = 0.045) at an intestine threshold level of 9.2 mg/kg (95% confidence interval 8.9-9.4, p value = 0.0016), which corresponds to 130.6 mg/kg of total Pb concentration in the soil. This is a narrow confidence interval for an important relationship.

Potential sources and racial disparities in the residential distribution of soil arsenic and lead among pregnant women.

Exposure to arsenic (As) or lead (Pb) has been associated with adverse health outcomes, and high-risk populations can be disproportionately exposed to these metals in soils. The objectives of this study were: to examine if predicted soil As and Pb concentrations at maternal residences of South Carolina (SC) low-income mothers differed based on maternal race (non-Hispanic black versus white), to examine whether differences in predicted residential soil As and Pb concentrations among black and white mothers differed by socioeconomic status (SES), and to examine whether such disparities persisted after controlling for anthropogenic sources of these metals, including direction from, and distance to industrial facilities. Kriged soil As and Pb concentrations were estimated at maternal residences in 11 locations in SC, and models with maternal race and individual and US Census block group level SES measures were examined. US Environmental Protection Agency Toxics Release Inventory (TRI) facility As and Pb releases categorized by distance and direction to block groups in which mothers resided were also identified, as were proxy measures for historic use of leaded gasoline (road density) and Pb-based paint (categories of median year home built by US Census block group). Consistent racial disparities were observed for predicted residential soil As and Pb concentrations, and the disparity was stronger for Pb than As (betas from adjusted models for black mothers were 0.12 and 2.2 for As and Pb, respectively, all p<0.006). Higher road density and older homes in block groups were more closely associated with higher predicted soil As and Pb concentrations than on-site releases of As and Pb categorized by facility location. These findings suggest that non-Hispanic black mothers in this study population had elevated residential As and Pb soil concentrations, after adjusting for SES, and that soil As and Pb concentrations were not associated with recent industrial releases.

A Bayesian semiparametric approach with change points for spatial ordinal data.

The change-point model has drawn much attention over the past few decades. It can accommodate the jump process, which allows for changes of the effects before and after the change point. Intellectual disability is a long-term disability that impacts performance in cognitive aspects of life and usually has its onset prior to birth. Among many potential causes, soil chemical exposures are associated with the risk of intellectual disability in children. Motivated by a study for soil metal effects on intellectual disability, we propose a Bayesian hierarchical spatial model with change points for spatial ordinal data to detect the unknown threshold effects. The spatial continuous latent variable underlying the spatial ordinal outcome is modeled by the multivariate Gaussian process, which captures spatial variation and is centered at the nonlinear mean. The mean function is modeled by using the penalized smoothing splines for some covariates with unknown change points and the linear regression for the others. Some identifiability constraints are used to define the latent variable. A simulation example is presented to evaluate the performance of the proposed approach with the competing models. A retrospective cohort study for intellectual disability in South Carolina is used as an illustration.

Bridging graduate education in public health and the liberal arts.

The University of Massachusetts Amherst is part of Five-Colleges Inc, a consortium that includes the university and four liberal arts colleges. Consortium faculty from the School of Public Health and Health Sciences at the university and from the colleges are working to bridge liberal arts with public health graduate education. We outline four key themes guiding this effort and exemplary curricular tools for innovative community-based and multidisciplinary academic and research programs. The structure of the consortium has created a novel trajectory for student learning and engagement, with important ramifications for pedagogy and professional practice in public health. We show how graduate public health education and liberal arts can, and must, work in tandem to transform public health practice in the 21st century.

Bayesian importance parameter modeling of misaligned predictors: soil metal measures related to residential history and intellectual disability in children.

In this paper, we propose a novel spatial importance parameter hierarchical logistic regression modeling approach that includes measurement error from misalignment. We apply this model to study the relationship between the estimated concentration of soil metals at the residence of mothers and the development of intellectual disability (ID) in their children. The data consist of monthly computerized claims data about the prenatal experience of pregnant women living in nine areas within South Carolina and insured by Medicaid during January 1, 1996 and December 31, 2001 and the outcome of ID in their children during early childhood. We excluded mother-child pairs if the mother moved to an unknown location during pregnancy. We identified an association of the ID outcome with arsenic (As) and mercury (Hg) concentration in soil during pregnancy, controlling for infant sex, maternal race, mother's age, and gestational weeks at delivery. There is some indication that Hg has a slightly higher importance in the third and fourth months of pregnancy, while As has a more uniform effect over all the months with a suggestion of a slight increase in risk in later months.

Associations between land cover categories, soil concentrations of arsenic, lead and barium, and population race/ethnicity and socioeconomic status.

The potential of using land cover/use categories as a proxy for soil metal concentrations was examined by measuring associations between Anderson land cover category percentages and soil concentrations of As, Pb, and Ba in ten sampling areas. Land cover category and metal associations with ethnicity and socioeconomic status at the United States Census 2000 block and block group levels also were investigated. Arsenic and Pb were highest in urban locations; Ba was a function of geology. Consistent associations were observed between urban/built up land cover, and Pb and poverty. Land cover can be used as proxy for metal concentrations, although associations are metal-dependent.

Are different soil metals near the homes of pregnant women associated with mild and severe intellectual disability in children?

AIM: We explored the association of relatively low concentrations of metals in the soil proximal to maternal residence during pregnancy, with intellectual disability. We hypothesized different metals would be associated with mild versus severe intellectual disability. METHOD: We used a mixed methods design, starting with a retrospective cohort from 1996 to 2002, of 10,051 pregnant mothers, soil sampling in the areas where these mothers resided during pregnancy, and follow-up of their children to determine if there was an intellectual disability outcome. We tested the soil and then predicted the soil concentration at the maternal homes, and modeled the association with the severity of the child's intellectual disability. RESULTS: We found a significant positive association between mild intellectual disability and soil mercury (p=0.007). For severe intellectual disability, there was a significant positive association with the soil arsenic and lead (p=0.025). INTERPRETATION: This is the first report of the differential impact of metals in soil and severity of intellectual disability in children. Soil mercury concentration in the area the mother lived during pregnancy is associated with significantly increased odds of mild intellectual disability; a combination of arsenic and lead is associated with significantly increased odds of severe intellectual disability. These associations are present when controlling for maternal, child, and neighborhood characteristics.

Does the metal content in soil around a pregnant woman's home increase the risk of low birth weight for her infant?

Low birth weight (LBW) is associated with a number of maternal environmental exposures during pregnancy. This study explored the association between soil metal concentrations around the home where the mother lived during pregnancy and the outcome of LBW. We used a retrospective cohort of 9,920 mother-child pairs who were insured by Medicaid during pregnancy and lived in ten residential areas, where we conducted soil sampling. We used a grid that overlaid the residential areas and collected soil samples at the grid intersections. The soil was analyzed for the concentration of eight metals [arsenic (As), barium (Ba), chromium (Cr), copper (Cu), lead (Pb), manganese (Mn), nickel (Ni), and mercury (Hg)], and we then used Bayesian Kriging to estimate the concentration at the actual maternal addresses, since we had the GIS coordinates of the homes. We used generalized additive modeling, because the metal concentrations had nonlinear associations with LBW, to develop the best fitting multivariable model for estimating the risk of LBW. The final model showed significant associations for female infants, maternal smoking during pregnancy, non-white mothers, Cu, and As with LBW. The As variable was nonlinear in relation to LBW, and the association between higher concentrations of As with LBW was strong (p = 0.002). We identified a statistically significant association between soil concentrations of arsenic around the home of pregnant women and an increased risk of LBW for her infant.

Temporal and spatial variation in residential soil metal concentrations: implications for exposure assessments.

Understanding temporal and spatial variation in soil chemicals is critical in exposure assessments. We measured eight metals in subsamples, duplicates (~0.3 m), and repeat soil samples taken 1-6 years after initial sampling (~5 m). We estimated variance components (VCs) of metal concentrations using nested analyses accounting for sampling area, land use and soil type, and calculated coefficients of variation (CVs) for repeat sample pairs. Total variance for all metals was similar, but VCs were proportioned differently by metal and sample type. Spatial variation explained the majority of variance in duplicate samples. CVs of metal concentrations were not significantly different over the long time interval, but repeat samples had larger VCs for unexplained error. Sampling area and land use were important for Ba and Mn, and Pb and Hg, respectively. Results suggest metals are stable over long times and suitable for exposure assessments, but that individual metal behavior should be considered.

Associations between soil lead concentrations and populations by race/ethnicity and income-to-poverty ratio in urban and rural areas.

Lead (Pb) is a well-studied environmental contaminant that has many negative health effects, especially for children. Both racial/ethnic and income disparities have been documented with respect to exposure to Pb in soils. The objectives of this study were to assess whether soil Pb concentrations in rural and urban areas of South Carolina USA, previously identified as having clusters of intellectual disabilities (ID) in children, were positively associated with populations of minority and low-income individuals and children (≤ 6 years of age). Surface soils from two rural and two urban areas with identified clusters of ID were analyzed for Pb and concentrations were spatially interpolated using inverse distance weighted analysis. Population race/ethnicity and income-to-poverty ratio (ITPR) from United States Census 2000 block group data were aerially interpolated by block group within each area. Urban areas had significantly higher concentrations of Pb than rural areas. Significant positive associations between black, non-Hispanic Latino, individuals and children ≤ 6 years of age and mean estimated Pb concentrations were observed in both urban (r = 0.38, p = 0.0007) and rural (r = 0.53, p = 0.04) areas. Significant positive associations also were observed between individuals and children with an ITPR < 1.00 and Pb concentrations, though primarily in urban areas. Racial/ethnic minorities and low ITPR individuals, including children, may be at elevated risk for exposure to Pb in soils.

Associations of estimated residential soil arsenic and lead concentrations and community-level environmental measures with mother-child health conditions in South Carolina.

We undertook a community-level aggregate analysis in South Carolina, USA, to examine associations between mother-child conditions from a Medicaid cohort of pregnant women and their children using spatially interpolated arsenic (As) and lead (Pb) concentrations in three geographic case areas and a control area. Weeks of gestation at birth was significantly negatively correlated with higher estimated As (r(s) = -0.28, p = 0.01) and Pb (r(s) = -0.26, p = 0.02) concentrations in one case area. Higher estimated Pb concentrations were consistently positively associated with frequency of black mothers (all p < 0.02) and negatively associated with frequency of white mothers (all p < 0.01), suggesting a racial disparity with respect to Pb.

The relationship between mental retardation and developmental delays in children and the levels of arsenic, mercury and lead in soil samples taken near their mother's residence during pregnancy.

This study was designed to evaluate the association between lead, mercury, and arsenic in the soil near maternal residences during pregnancy and mental retardation or developmental disability (MR/DD) in children. The study was conducted using 6,048 mothers who did not move throughout their pregnancies and lived within six strips of land in South Carolina and were insured by Medicaid between January 1, 1997 and December 31, 2002. The mother child pairs were then followed until June 1, 2008, through their Medicaid reimbursement files, to identify children diagnosed with MR/DD. The soil was sampled for mercury (Hg), lead (Pb), and As based on a uniform grid, and the soil concentrations were Kriged to estimate chemical concentration at individual locations. We identified a significant relationship between MR/DD and As, and the form of the relationship was nonlinear, after controlling for other known risk factors.

Bayesian spatial modeling of disease risk in relation to multivariate environmental risk fields.

The relationship between exposure to environmental chemicals during pregnancy and early childhood development is an important issue that has a spatial risk component. In this context, we have examined mental retardation and developmental delay (MRDD) outcome measures for children in a Medicaid population in South Carolina and sampled measures of soil chemistry (e.g. As, Hg, etc.) on a network of sites that are misaligned to the outcome residential addresses during pregnancy. The true chemical concentration at the residential addresses is not observed directly and must be interpolated from soil samples. In this study, we have developed a Bayesian joint model that interpolates soil chemical fields and estimates the associated MRDD risk simultaneously. Having multiple spatial fields to interpolate, we have considered a low-rank Kriging method for the interpolation that requires less computation than the Bayesian Kriging. We performed a sensitivity analysis for a bivariate smoothing, changing the number of knots and the smoothing parameter. These analyses show that a low-rank Kriging method can be used as an alternative to a full-rank Kriging, reducing the computational burden. However, the number of knots for the low-rank Kriging model needs to be selected with caution as a bivariate surface estimation can be sensitive to the choice of the number of knots.

Identifying natural and anthropogenic sources of metals in urban and rural soils using GIS-based data, PCA, and spatial interpolation.

Determining sources of neurotoxic metals in rural and urban soils is important for mitigating human exposure. Surface soil from four areas with significant clusters of mental retardation and developmental delay (MR/DD) in children, and one control site were analyzed for nine metals and characterized by soil type, climate, ecological region, land use and industrial facilities using readily available GIS-based data. Kriging, principal component analysis (PCA) and cluster analysis (CA) were used to identify commonalities of metal distribution. Three MR/DD areas (one rural and two urban) had similar soil types and significantly higher soil metal concentrations. PCA and CA results suggested that Ba, Be and Mn were consistently from natural sources; Pb and Hg from anthropogenic sources; and As, Cr, Cu, and Ni from both sources. Arsenic had low commonality estimates, was highly associated with a third PCA factor, and had a complex distribution, complicating mitigation strategies to minimize concentrations and exposures.

Soil metal concentrations and toxicity: associations with distances to industrial facilities and implications for human health.

Urban and rural areas may have different levels of environmental contamination and different potential sources of exposure. Many metals, i.e., arsenic (As), lead (Pb), and mercury (Hg), have well-documented negative neurological effects, and the developing fetus and young children are particularly at risk. Using a database of mother and child pairs, three areas were identified: a rural area with no increased prevalence of mental retardation and developmental delay (MR/DD) (Area A), and a rural area (Area B) and an urban area (Area C) with significantly higher prevalence of MR/DD in children as compared to the state-wide average. Areas were mapped and surface soil samples were collected from nodes of a uniform grid. Samples were analyzed for As, barium (Ba), beryllium (Be), chromium (Cr), copper (Cu), Pb, manganese (Mn), nickel (Ni), and Hg concentrations and for soil toxicity, and correlated to identify potential common sources. ArcGIS was used to determine distances between sample locations and industrial facilities, which were correlated with both metal concentrations and soil toxicity. Results indicated that all metal concentrations (except Be and Hg) in Area C were significantly greater than those in Areas A and B (p< or =0.0001) and that Area C had fewer correlations between metals suggesting more varied sources of metals than in rural areas. Area C also had a large number of facilities whose distances were significantly correlated with metals, particularly Cr (maximum r=0.33; p=0.0002), and with soil toxicity (maximum r=0.25; p=0.007) over a large spatial scale. Arsenic was not associated with distance to any facility and may have a different anthropogenic, or natural source. In contrast to Area C, both rural areas had lower concentrations of metals, lower soil toxicity, and a small number of facilities with significant associations between distance and soil metals.

Application of encapsulation (pH-sensitive polymer and phosphate buffer macrocapsules): a novel approach to remediation of acidic ground water.

Macrocapsules, composed of a pH-sensitive polymer and phosphate buffer, offer a novel remediation alternative for acidic ground waters. To test their potential effectiveness, laboratory experiments were carried out followed by a field trial within a coal pile runoff (CPR) acidic contaminant plume. Results of traditional limestone and macrocapsule treatments were compared in both laboratory and field experiments. Macrocapsules were more effective than limestone as a passive treatment for raising pH in well water from 2.5 to 6 in both laboratory and field experiments. The limestone treatments had limited impact on pH, only increasing pH as high as 3.3, and armoring by iron was evident in the field trial. Aluminum, iron and sulfate concentrations remained relatively constant throughout the experiments, but phosphate increased (0.15-32 mg/L), indicating macrocapsule release. This research confirmed that macrocapsules may be an effective alternative to limestone to treat highly acidic ground water.