A Review of Metal Exposure Studies Conducted in the Rural Southwestern and Mountain West Region of the United States

Preterm Birth and Metal Mixture Exposure among Pregnant Women from the Navajo Birth Cohort Study

BACKGROUND

Preterm birth (PTB), defined as birth before 37 wk gestation, is associated with hypertension, diabetes, inadequate prenatal care, unemployment or poverty, and metal exposure. Indigenous individuals are more likely to have maternal risk factors associated with PTB compared with other populations in the United States; however, the role of environmental metals on PTB among pregnant Indigenous women remains uncertain. Previous research identified associations between PTB and individual metals, but there is limited investigation on metal mixtures and this birth outcome.

OBJECTIVES

We used a mixtures analysis framework to investigate the association between metal mixtures and PTB among pregnant Indigenous women from the Navajo Birth Cohort Study (NBCS).

METHODS

Maternal urine and blood samples were collected at the time of study enrollment and analyzed for metals by inductively coupled plasma dynamic reaction cell mass spectrometry. Bayesian Profile Regression was used to identify subgroups (clusters) of individuals with similar patterns of coexposure and to model association with PTB.

RESULTS

Results indicated six subgroups of maternal participants with distinct exposure profiles, including one group with low exposure to all metals and one group with total arsenic, cadmium, lead, and uranium concentrations exceeding representative concentrations calculated from the National Health and Nutrition Examination Survey (NHANES). Compared with the reference group (i.e., the lowest exposure subgroup), the subgroup with the highest overall exposure had a relative risk of PTB of 2.9 times (95% credible interval: 1.1, 6.1). Exposures in this subgroup were also higher overall than NHANES median values for women 14-45 years of age.

DISCUSSION

Given the wide range of exposures and elevated PTB risk for the most exposed subgroups in a relatively small study, follow-up investigation is recommended to evaluate associations between metal mixture profiles and other birth outcomes and to test hypothesized mechanisms of action for PTB and oxidative stress caused by environmental metals. https://doi.org/10.1289/EHP10361.

Meteorological data source comparison-a case study in geospatial modeling of potential environmental exposure to abandoned uranium mine sites in the Navajo Nation

Meteorological (MET) data is a crucial input for environmental exposure models. While modeling exposure potential using geospatial technology is a common practice, existing studies infrequently evaluate the impact of input MET data on the level of uncertainty on output results. The objective of this study is to determine the effect of various MET data sources on the potential exposure susceptibility predictions. Three sources of wind data are compared: The North American Regional Reanalysis (NARR) database, meteorological aerodrome reports (METARs) from regional airports, and data from local MET weather stations. These data sources are used as inputs into a machine learning (ML) driven GIS Multi-Criteria Decision Analysis (GIS-MCDA) geospatial model to predict potential exposure to abandoned uranium mine sites in the Navajo Nation. Results indicate significant variations in results derived from different wind data sources. After validating the results from each source using the National Uranium Resource Evaluation (NURE) database in a geographically weighted regression (GWR), METARs data combined with the local MET weather station data showed the highest accuracy, with an average R2 of 0.74. We conclude that local direct measurement-based data (METARs and MET data) produce a more accurate prediction than the other sources evaluated in the study. This study has the potential to inform future data collection methods, leading to more accurate predictions and better-informed policy decisions surrounding environmental exposure susceptibility and risk assessment.

Mangrove (Avicennia marina) parts as proxies in marine pollution of Nizampatnam Bay, East Coast of India: An integrated approach

This study focuses on the assessment of heavy metals (HM) concentration and pollution status of the Nizampatnam Bay, east coast of India, from mangrove plant parts (roots and leaves) and sediment samples. This is the first of its kind work (comparison of data from both mangrove and sediment samples) from the third largest mangrove ecosystem in India. To carry out this work, plant (Avicennia mariana) and sediment samples were collected from five stations. The collected samples were carefully subjected to the laboratory methods and heavy metal concentrations were determined by using inductively coupled plasma-optical emission spectroscopy (ICP-OES). The obtained results were juxtaposed with the optimal values of world surface pollution rock averages, and noticed heavy metals such as Cd and Cu exceed the optimal values. To know the contamination levels and the chemical elements that contribute to the pollution, various environmental indices, viz., contamination factor, enrichment factor, geoaccumulation index, and pollution load index were, carried out on the sediment sample data. To ascertain the mangrove plant's capacity (in the study area) for accumulation and translocation of heavy metals in different parts of the plants, factors such as bio-concentration and translocation were calibrated.

Chronic Community Exposure to Environmental Metal Mixtures Is Associated with Selected Cytokines in the Navajo Birth Cohort Study (NBCS)

Many tribal populations are characterized by health disparities, including higher rates of infection, metabolic syndrome, and cancer-all of which are mediated by the immune system. Members of the Navajo Nation have suffered chronic low-level exposure to metal mixtures from uranium mine wastes for decades. We suspect that such metal and metalloid exposures lead to adverse health effects via their modulation of immune system function. We examined the relationships between nine key metal and metalloid exposures (in blood and urine) with 11 circulating biomarkers (cytokines and CRP in serum) in 231 pregnant Navajo women participating in the Navajo Birth Cohort Study. Biomonitored levels of uranium and arsenic species were considerably higher in participants than NHANES averages. Each biomarker was associated with a unique set of exposures, and arsenic species were generally immunosuppressive (decreased cellular and humoral stimulating cytokines). Overall, our results suggest that environmental metal and metalloid exposures modulate immune status in pregnant Navajo women, which may impact long-term health outcomes in mothers and their children.

Implementation of Indigenous Food Tax Policies in Stores on Navajo Nation

In 2014, the Navajo Nation Healthy Diné Nation Act (HDNA) was enacted and permanently approved in 2020; HDNA places a 2% surtax on unhealthy foods and beverages, while other 2014 legislation exempted healthy food items from the 6% regular sales tax. Little is known about Navajo Nation store manager/owner perspectives toward the HDNA and how best to support stores to implement the legislation. Purposive sampling was used to ensure a balanced sample of correct HDNA implementers, incorrect HDNA implementers, and stores which made healthy store changes over the past 6 years. Three community-based interviewers collected surveys by phone or in-person. Frequency of closed-ended questions was quantified, and open-ended responses were coded using thematic analysis. Of 29 identified sample stores, 20 were interviewed to reach saturation. Eleven of 20 stores made changes improving their healthy food environments. Barriers included lack of equipment (6/20) and low consumer demand (5/20). Facilitators included consumer awareness and increased produce supply options (5/20). Sixteen of 20 stores supported HDNA continuation. Facilitators to HDNA implementation included orientation and informational materials (6/20) and promotion of tax-free items (5/20). Barriers included confusion about the tax (6/20) and tax exemption (5/20). Suggestions for support included printed materials (6/20) and store training (5/20). HDNA benefits included greater awareness of healthy choices among staff (7/20) and customer-community members (2/20). Most managers and owners expressed receiving support for healthy store changes and HDNA, but also identified a need for added resources and support. Findings inform legislative action to promote timely and appropriate uptake of HDNA, and support equitable, healthy food systems.

Metal(loid)s in Common Medicinal Plants in a Uranium Mining-Impacted Area in Northwestern New Mexico, USA

The objective of this study was to determine uranium (U) and other metal(loid) concentrations (As, Cd, Cs, Pb, Mo, Se, Th, and V) in eight species of plants that are commonly used for medicinal purposes on Diné (Navajo) lands in northwestern New Mexico. The study setting was a prime target for U mining, where more than 500 unreclaimed abandoned U mines and structures remain. The plants were located within 3.2 km of abandoned U mines and structures. Plant biota samples (N = 32) and corresponding soil sources were collected. The samples were analyzed using Inductively Coupled Plasma−Mass Spectrometry. In general, the study findings showed that metal(loid)s were concentrated greatest in soil > root > aboveground plant parts, respectively. Several medicinal plant samples were found to exceed the World Health Organization Raw Medicinal Plant Permissible Level for As and Cd; however, using the calculated human intake data, Reference Dietary Intakes, Recommended Dietary Allowances, and tolerable Upper Limits, the levels were not exceeded for those with established food intake or ingestion guidelines. There does not appear to be a dietary food rise of metal(loid) ingestion based solely on the eight medicinal plants examined. Food intake recommendations informed by research are needed for those who may be more sensitive to metal(loid) exposure. Further research is needed to identify research gaps and continued surveillance and monitoring are recommended for mining-impacted communities.

Association between prenatal exposure to metal mixtures and early childhood allergic diseases

The association between prenatal exposure to the metal mixture and allergic diseases is poorly understood. We aimed to explore the individual effect and the combined effect of prenatal exposure to vanadium (V), chromium (Cr), nickel (Ni), arsenic (As), cadmium (Cd), thallium (Tl), and lead (Pb) on early childhood allergic diseases based on a birth cohort study that included 628 mother-infant pairs. Metals were measured in maternal urine samples collected in the first, second, and third trimesters. Children were prospectively followed up at age 4 years to collect information on allergic rhinitis, wheeze, and eczema status. By applying logistic regression models, weighted quantile sum (WQS) regression, and Bayesian kernel machine regression (BKMR), the different statistical analyses revealed urinary metals were only associated with early childhood allergic rhinitis. The averaged prenatal As exposure was significantly associated with an increased OR for allergic rhinitis in both single-metal (OR = 2.04, 95% CI: 1.35, 3.07) and multiple-metal logistic regression models (OR = 1.78, 95% CI: 1.15, 2.78). The WQS index of mixed metal exposure was positively associated with allergic rhinitis (OR = 1.66, 95% CI: 1.26, 2.19), and As and Tl had the largest weights in the WQS index (weighted 0.51 and 0.29, respectively). The BKMR analysis also showed the overall effect of the metal mixture was significantly associated with allergic rhinitis when all the metals were at their 55th percentile or above, compared to their 50th percentile. The effect of As and Tl on the risk of allergic rhinitis was significant when all of the other metals were fixed at the specific percentiles. Our findings suggest that prenatal co-exposure to higher levels of the seven metals increases the risk of allergic rhinitis in children, and As and Tl may contribute most to the combined risk.

A Secure and Reusable Software Architecture for Supporting Online Data Harmonization

Retrospective data harmonization across multiple research cohorts and studies is frequently done to increase statistical power, provide comparison analysis, and create a richer data source for data mining. However, when combining disparate data sources, harmonization projects face data management and analysis challenges. These include differences in the data dictionaries and variable definitions, privacy concerns surrounding health data representing sensitive populations, and lack of properly defined data models. With the availability of mature open-source web-based database technologies, developing a complete software architecture to overcome the challenges associated with the harmonization process can alleviate many roadblocks. By leveraging state-of-the-art software engineering and database principles, we can ensure data quality and enable cross-center online access and collaboration. This paper outlines a complete software architecture developed and customized using the Django web framework, leveraged to harmonize sensitive data collected from three NIH-support birth cohorts. We describe our framework and show how we successfully overcame challenges faced when harmonizing data from these cohorts. We discuss our efforts in data cleaning, data sharing, data transformation, data visualization, and analytics, while reflecting on what we have learned to date from these harmonized datasets.

Environmental risk mapping of potential abandoned uranium mine contamination on the Navajo Nation, USA, using a GIS-based multi-criteria decision analysis approach

The Navajo Nation (NN), a sovereign indigenous tribal nation in the Southwestern United States, is home to 523 abandoned uranium mines (AUMs). Previous health studies have articulated numerous human health hazards associated with AUMs and multiple environmental mechanisms/pathways (e.g., air, water, and soil) for contaminant transport. Despite this evidence, the limited modeling of AUM contamination that exists relies solely on proximity to mines and only considers single rather than combined pathways from which the contamination is a product. In order to better understand the spatial dynamics of contaminant exposure across the NN, we adopted the following established geospatial and computational methods to develop a more sophisticated environmental risk map illustrating the potential for AUM contamination: GIS-based multi-criteria decision analysis (GIS-MCDA), fuzzy logic, and analytic hierarchy process (AHP). Eight criteria layers were selected for the GIS-MCDA model: proximity to AUMs, roadway proximity, drainage proximity, topographic landforms, wind index, topographic wind exposure, vegetation index, and groundwater contamination. Model sensitivity was evaluated using the one-at-a-time method, and statistical validation analysis was conducted using two separate environmental datasets. The sensitivity analysis indicated consistency and reliability of the model. Model results were strongly associated with environmental uranium concentrations. The model classifies 20.2% of the NN as high potential for AUM contamination while 65.7% and 14.1% of the region are at medium and low risk, respectively. This study is entirely a novel application and a crucial first step toward informing future epidemiologic studies and ongoing remediation efforts to reduce human exposure to AUM waste.

Metal(loid)s in Cucurbita pepo in a Uranium Mining Impacted Area in Northwestern New Mexico, USA

More than 500 unreclaimed mines and associated waste sites exist on the Navajo Nation reservation as a result of uranium (U) mining from the 1940s through the 1980s. For this study, the impact of U-mine waste on a common, locally grown crop food was examined. The goal of this site-specific study was to determine metal(loid) concentration levels of arsenic (As), cadmium (Cd), cesium (Cs), molybdenum (Mo), lead (Pb), thorium (Th), U, vanadium (V) and selenium (Se) in Cucurbita pepo Linnaeus (squash), irrigation water, and soil using inductively coupled plasma-mass spectrometry. The concentrations of metal(loid)s were greatest in roots > leaves > edible fruit (p < 0.05), respectively. There were significant differences between metal(loid)s in squash crop plot usage (<5 years versus >30 years) for V (p = 0.001), As (p < 0.001), U (p = 0.002), Cs (p = 0.012), Th (p = 0.040), Mo (p = 0.047), and Cd (p = 0.042). Lead and Cd crop irrigation water concentrations exceeded the United States Environmental Protection Agency (USEPA) Maximum Contaminant Levels for drinking water for those metals. Edible squash concentration levels were 0.116 mg/kg of As, 0.248 mg/kg of Pb, 0.020 mg/kg of Cd, and 0.006 mg/kg of U. Calculated human ingestion of edible squash did not exceed Provisional Tolerable Weekly Intake or Tolerable Upper Limit levels from intake based solely on squash consumption. There does not appear to be a food-ingestion risk from metal(loid)s solely from consumption of squash. Safer access and emphasis on consuming regulated water was highlighted. Food intake recommendations were provided. Continued monitoring, surveillance, and further research are recommended.