Journal of Exposure Science and Environmental Epidemiology最新文献

Background

Geospatial methods are common in environmental exposure assessments and increasingly integrated with health data to generate comprehensive models of environmental impacts on public health.

Objective

Our objective is to review geospatial exposure models and approaches for health data integration in environmental health applications.

Methods

We conduct a literature review and synthesis.

Results

First, we discuss key concepts and terminology for geospatial exposure data and models. Second, we provide an overview of workflows in geospatial exposure model development and health data integration. Third, we review modeling approaches, including proximity-based, statistical, and mechanistic approaches, across diverse exposure types, such as air quality, water quality, climate, and socioeconomic factors. For each model type, we provide descriptions, general equations, and example applications for environmental exposure assessment. Fourth, we discuss the approaches used to integrate geospatial exposure data and health data, such as methods to link data sources with disparate spatial and temporal scales. Fifth, we describe the landscape of open-source tools supporting these workflows.

Background: Ambient O₃ has demonstrated an aggravated increasing trend in the context of global warming. The available evidence of maternal exposure to ambient O₃ on fetal congenital heart defects (CHD) is still limited, especially in high polluted areas.

Objective: To examine associations of maternal exposure to ambient O₃ during early pregnancy with fetal CHDs.

Methods: We conducted a national multicenter study in 1313 hospitals from 26 provinces in China and collected a total of 27,817 participants at high risk of CHD from 2013 to 2021. Exposure to ambient O₃ during the embryonic period, preconception, the first trimester and periconception was assessed by extracting daily concentrations from a validated grid dataset at each subject's residential district. CHDs were diagnosed based on fetal echocardiography.

Results: Each 10 µg/m³ increase of exposure to ambient O₃ during the embryonic period was approximately linearly associated with a 12.7% (odds ratio [OR]: 1.127, 95% confidence interval [CI]: 1.098, 1.155) increase in odds of pooled CHD (p < 0.001). The associations remain robust after adjusting for ambient PM_2.5 and NO₂ exposure. The odds of different types of CHD in association with ambient O₃ exposure varied greatly. We observed significant association of ambient O₃ exposure with ventricular septal defect (VSD), tetralogy of Fallot (TOF); pulmonary stenosis (PS), pulmonary atresia (PA), transposition of great arteries (TGA) and persistent left superior vena cava (PLSVC), with TOF demonstrating the strongest estimates (OR: 1.194, 95% CI:1.107, 1.288). The estimates for preconception, the first trimester and periconception demonstrate consistent findings with the main analyses, indicating stronger associations of ambient O₃ exposure during the periconception period.

Impact: Our study provides evidence that higher ambient O₃ during early pregnancy was significantly associated with increased odds of fetal CHD. Our findings suggest that pregnant women, clinical practitioners, and policy makers need to pay more attention to the exposure to higher ambient O₃ during early pregnancy to reduce the risk of developing CHD and to improve outcomes across the life span.

Introduction: In 2019 the World Health Organisation published a report which concluded microplastics in drinking water did not present a threat to human health. Since this time a plethora of research has emerged demonstrating the presence of plastic in various organ systems and their deleterious pathophysiological effects.

Methods: A scoping review was undertaken in line with recommendations from the Johanna Briggs Institute. Five databases (PubMed, SCOPUS, CINAHL, Web of Science and EMBASE) were systematically searched in addition to a further grey literature search.

Results: Eighteen articles were identified, six of which investigated and characterised the presence of microplastics and nanoplastics (MNPs) in the human urinary tract. Microplastics were found to be present in kidney, urine and bladder cancer samples. Twelve articles investigated the effect of MNPs on human cell lines associated with the human urinary tract. These articles suggest MNPs have a cytotoxic effect, increase inflammation, decrease cell viability and alter mitogen-activated protein kinases (MAPK) signalling pathways.

Conclusion: Given the reported presence MNPs in human tissues and organs, these plastics may have potential health implications in bladder disease and dysfunction. As a result, institutions such as the World Health Organisation need to urgently re-evaluate their position on the threat of microplastics to public health.

Impact statement: This scoping review highlights the rapidly emerging threat of microplastic contamination within the human urinary tract, challenging the World Health Organisation's assertion that microplastics pose no risk to public health. The documented cytotoxic effects of microplastics, alongside their ability to induce inflammation, reduce cell viability and disrupt signalling pathways, raise significant public health concerns relating to bladder cancer, chronic kidney disease, chronic urinary tract infections and incontinence. As a result, this study emphasises the pressing need for further research and policy development to address the challenges surrounding microplastic contamination.

Addressing complex environmental health challenges necessitates the integration of multiple research methodologies to fully understand the social, economic, and health impacts of exposure to environmental hazards. Qualitative and mixed methods (QMM) are vital in uncovering the sociocultural dynamics that influence people's interactions with their environment and subsequent health-related outcomes. QMM has the potential to reveal insights that quantitative methods might overlook. However, QMM approaches have been underutilized in exposure science, with less than 1% of the studies published in the Journal of Exposure Science and Environmental Epidemiology (JESEE) from 2003 to 2023 employing these methods. JESEE studies that utilized QMM have enhanced exposure assessment, explored risk perceptions, and evaluated the impact of interventions, particularly among historically marginalized populations. QMM approaches have addressed gaps in traditional exposure assessment by allowing researchers to capture nuanced perspectives often missed by quantitative analyses, especially in understanding the lived experiences of affected communities. Exposure scientists are encouraged to adopt QMM to advance more comprehensive and inclusive approaches to studying and mitigating environmental risks. Fostering interdisciplinary collaborations that integrate the social sciences can enhance the development of robust, context-sensitive solutions to environmental health challenges.

Background: Subways are popular and efficient modes of transportation in cities. However, people are exposed to high levels of particulate matter (PM) in subways. Subway air quality in the United States has been investigated in a few cities, but data is lacking on simultaneous measurement of several pollutants, especially ultrafine particles (UFP) and black carbon (BC), in combination with different size fractions of PM.

Objectives: The goals of this study are to assess air quality in a belowground subway and compare it with outdoor ambient levels, to examine temporal variability of PM in the subway, and to analyze the correlation between PM and BC.

Methods: Particulate matter of varying sizes (PM₁, PM_2.5, PM₁₀), UFP, and BC were measured using DustTrak, nanoparticle detector, and micro aethalometer, respectively. Measurements were made at the belowground subway platform and the aboveground street level at 15th Street subway station in Philadelphia during summer 2022.

Results: Belowground mean PM₁, PM_2.5, and PM₁₀ were 112.2 ± 61.3 µg/m³, 120 ± 65.5 µg/m³, and 182.1 ± 132 µg/m³, respectively, which were 5.4, 5.7, and 7.6 times higher than the respective aboveground street levels. The UFP lung deposited surface area (LDSA) (59.4 ± 36.2 µm²/cm³) and BC (9.5 ± 5.4 μg/m³) belowground were 1.7 times and 10.7 times higher than the aboveground. The pollutant concentration varied from day-to-day on both the locations. A higher positive correlation was found between the belowground BC and PM_2.5 (r = 0.51, p < 0.05) compared to the aboveground (r = 0.16, p < 0.05).

Impact: This study showed high levels of particulate matter exposure at a belowground subway station in Philadelphia. Particulate matter levels were about 5 to 8 times higher at belowground subway station than the corresponding aboveground street level. Higher levels were also observed for UFP lung deposited surface area (LDSA), while black carbon levels showed the highest concentration at the belowground level by a factor of ten compared to the aboveground level. The study shows the need for air quality management at belowground subways to reduce particulate matter exposure for the commuters.

Background: Influenza healthcare encounters in adults associated with specific sources of PM_2.5 is an area of active research.

Objective: Following 2017 legislation requiring reductions in emissions from light-duty vehicles, we hypothesized a reduced rate of influenza healthcare encounters would be associated with concentrations of PM_2.5 from traffic sources in the early implementation period of this regulation (2017-2019).

Methods: We used the Statewide Planning and Research Cooperative System (SPARCS) to study adult patients hospitalized (N = 5328) or treated in the emergency department (N = 18,247) for influenza in New York State. Using a modified case-crossover design, we estimated the excess rate (ER) of influenza hospitalizations and emergency department visits associated with interquartile range increases in source-specific PM_2.5 concentrations (e.g., spark-ignition emissions [GAS], biomass burning [BB], diesel [DIE]) in lag day(s) 0, 0-3 and 0-6. We then evaluated whether ERs differed after Tier 3 implementation (2017-2019) compared to the period prior to implementation (2014-2016).

Results: Each interquartile range increase in DIE in lag days 0-6 was associated with a 21.3% increased rate of influenza hospitalization (95% CI: 6.9, 37.6) in the 2014-2016 period, and a 6.3% decreased rate (95% CI: -12.7, 0.5) in the 2017-2019 period. The GAS/influenza excess rates were larger in the 2017-2019 period than the 2014-2016 period for emergency department visits. We also observed a larger ER associated with increased BB in the 2017-2019 period compared to the 2014-2016 period.

Impact statement: We present an accountability study on the impact of the early implementation period of the Tier 3 vehicle emission standards on the association between specific sources of PM_2.5 air pollution on influenza healthcare encounters in New York State. We found that the association between gasoline emissions and influenza healthcare encounters did not lessen in magnitude between periods, possibly because the emissions standards were not yet fully implemented. The reduction in the rates of influenza healthcare encounters associated with diesel emissions may be reflective of past policies to reduce the toxicity of diesel emissions. Accountability studies can help policy makers and environmental scientists better understand the timing of pollution changes and associated health effects.

Background: Pyrotechnic displays often lead to significant increases in poor air quality. The widespread environmental fate-involving air, water, and spatial-temporal analyses-of fireworks-produced pollutants has seldom been investigated.

Objective: This study examined the environmental fate of pollutants from the largest fireworks event in the U.S.: Macy's Fourth of July Fireworks show in New York City (NYC).

Methods: Real-time PM_2.5 and gravimetric PM_2.5 and PM₁₀ were collected at locations along the East River of NYC. Airborne particles were assayed for trace elements (X-ray fluorescence) and organic and elemental carbon (OC/EC). River water samples were evaluated by ICP-MS for heavy-metal water contamination. Spatial-temporal analyses were created using PM_2.5 concentrations reported by both EPA and PurpleAir monitoring networks for NYC and 5 other major metropolitan areas.

Results: The fireworks event resulted in large increases in PM_2.5 mass concentrations at the river-adjacent sampling locations. While background control PM_2.5 was 10-15 µg/m³, peak real-time PM_2.5 levels exceeded 3000 µg/m³ at one site and 1000 µg/m³ at two other locations. The integrated gravimetric PM_2.5 and PM₁₀ concentrations during the fireworks event ranged from 162 to 240 µg/m³ and 252 to 589 µg/m³, respectively. Zn, Pb, Sb, and Cu more than doubled in river water samples taken after the event, while S, K, Ba, Cu, Mg, Fe, Sr, Ti, and Zn increased in airborne PM_2.5 from the fireworks. Data from hyperlocal monitoring networks for NYC and other metropolitan areas yielded similar, but generally smaller, increases in PM_2.5 levels.

Impact: Fireworks shows have been associated with environmental contamination. This comprehensive analysis considers the fate of pollutants from the largest annual U.S. pyrotechnic show through air, water, and hyperlocal temporal characterization.

Background: The United States Environmental Protection Agency (USEPA) regulates over 80 contaminants in community water systems (CWS), including those relevant to infant health outcomes. Multi-cohort analyses of the association between measured prenatal public water contaminant concentrations and infant health outcomes are sparse in the US.

Objective: Our objectives were to (1) develop Zip Code Tabulation Area (ZCTA)-level CWS contaminant concentrations for participants in the Environmental Influences on Child Health Outcomes (ECHO) Cohort and (2) evaluate regional, seasonal, and sociodemographic inequities in contaminant concentrations at the ZCTA-level. The ECHO Cohort harmonizes data from over 69 extant pregnancy and pediatric cohorts across the US.

Methods: We used CWS estimates derived from the USEPA's Six-Year Review 3 (2006-2011) to develop population-weighted, average concentrations for 10 contaminants across 7640 ZCTAs relevant to the ECHO Cohort. We evaluated contaminant distributions, exceedances of regulatory thresholds, and geometric mean ratios (with corresponding percent changes) associated with ZCTA sociodemographic characteristics via spatial lag linear regression models.

Results: We observed significant regional variability in contaminant concentrations across the US. ZCTAs were most likely to exceed the maximum contaminant level for arsenic (n = 100, 1.4%) and the health-protective threshold for total trihalomethanes (n = 3584, 64.0%). A 10% higher proportion of residents who were American Indian/Alaskan Native and Hispanic/Latino was associated with higher arsenic (11%, 95% CI: 7%, 15%; and 2%, 95% CI: 0%, 3%, respectively) and uranium (15%, 95% CI: 10%, 21%; and 9%, 95% CI: 6%, 12%, respectively) concentrations.

Impact: Nationwide epidemiologic analyses evaluating the association between US community water system contaminant concentration estimates and associated adverse birth outcomes in cohort studies are sparse because public water contaminant concentration estimates that can be readily linked to participant addresses are not available. We developed Zip Code Tabulation Area (ZCTA)-level CWS contaminant concentrations that can be linked to participants in the Environmental Influences on Child Health Outcomes (ECHO) Cohort and evaluated regional, seasonal, and sociodemographic inequities in contaminant concentrations for these ZCTAs. Future epidemiologic studies can leverage these CWS exposure estimates in the ECHO Cohort to evaluate associations with relevant infant outcomes.

Background: Per and polyfluoroalkyl substances (PFAS), a class of environmentally and biologically persistent chemicals, have been used across many industries since the middle of the 20^th century. Some PFAS have been linked to adverse health effects.

Objective: Our objective was to incorporate known and potential PFAS sources, physical characteristics of the environment, and existing PFAS water sampling results into a PFAS risk prediction map that may be used to develop a PFAS water sampling prioritization plan for the Colorado Department of Public Health and Environment (CDPHE).

Methods: We used random forest classification to develop a predictive surface of potential groundwater contamination from two PFAS, perfluorooctane sulfonate (PFOS) and perfluorooctanoate (PFOA). The model predicted PFAS risk at locations without sampling data into one of three risk categories after being "trained" with existing PFAS water sampling data. We used prediction results, variable importance ranking, and population characteristics to develop recommendations for sampling prioritization.

Results: Sensitivity and precision ranged from 58% to 90% in the final models, depending on the risk category. The model and prioritization approach identified private wells in specific census blocks, as well as schools, mobile home parks, and public water systems that rely on groundwater as priority sampling locations. We also identified data gaps including areas of the state with limited sampling and potential source types that need further investigation.

Impact statement: This work uses random forest classification to predict the risk of groundwater contamination from two per- and polyfluoroalkyl substances (PFAS) across the state of Colorado, United States. We developed the prediction model using data on known and potential PFAS sources and physical characteristics of the environment, and "trained" the model using existing PFAS water sampling results. This data-driven approach identifies opportunities for PFAS water sampling prioritization as well as information gaps that, if filled, could improve model predictions. This work provides decision-makers information to effectively use limited resources towards protection of populations most susceptible to the impacts of PFAS exposure.