Public drinking water contaminant estimates for birth cohorts in the Environmental Influences on Child Health Outcomes (ECHO) Cohort.

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.

Electric buses as an air pollution and meteorological observation network: Methodology and preliminary results.

Many local agencies in the United States and other countries are tasked to install air pollution monitoring systems of highly accurate sensors that have high acquisition, operating, and maintenance costs. The need for expanded coverage of air quality measurements across Salt Lake County (SLCO), Utah is being met by mounting air quality and temperature sensors on an expanding fleet of battery electric buses (BEBs). Monitoring air quality from a mobile sensor network provides real-time insights into air pollution patterns at high temporal and spatial resolution. Mobile measurements contribute to assessing residents' exposure to air pollution, facilitating the implementation of cost-effective public health policies and highlighting disparities. The Electric Bus Air Quality Observation Project was launched in SLCO during July 2021 and has collected millions of observations to date. A BEB traveling at typical traffic speeds (~10 m s-1) can provide multiple measurements along city block lengths of up to ~200 m. With careful analysis that factors in the time response of the differing sensors, variability from block-to-block may be attributed to fine-scale factors (e.g., pollution and heat sources, tree shading and urban vegetation, etc.). Preliminary findings showcase the value of increased coverage and resolution. During an extreme heat event in July 2023, both the morning and afternoon temperature readings showed differences of over 6.5 °C (12 °F), primarily as an east-west gradient with similar gradients in ozone. We conclude that temperature and pollutant concentration readings, at fine spatial and temporal resolutions, will facilitate future health studies and equitable policy and mitigation strategies. Our study demonstrates that our partnerships established with governmental, non-profit, and transit agencies facilitate the successful transfer of research and development to operational real-time mobile air quality monitoring.

Designing Retirement Strategies for Coal-Fired Power Plants To Mitigate Air Pollution and Health Impacts.

Retiring coal power plants can reduce air pollution and health damages. However, the spatial distribution of those impacts remains unclear due to complex power system operations and pollution chemistry and transport. Focusing on coal retirements in Pennsylvania (PA), we analyze six counterfactual scenarios for 2019 that differ in retirement targets (e.g., reducing 50% of coal-based installed capacity vs generation) and priorities (e.g., closing plants with higher cost, closer to Environmental Justice Areas, or with higher CO2 emissions). Using a power system model of the PJM Interconnection, we find that coal retirements in PA shift power generation across PA and Rest of PJM, leading to scenario-varying changes in the plant-level release of air pollutants. Considering pollution transport and the size of the exposed population, these emissions changes, in turn, give rise to a reduction of 6-136 PM2.5-attributable deaths in PJM across the six scenarios, with most reductions occurring in PA. Among our designed scenarios, those that reduce more coal power generation yield greater aggregate health benefits due to air quality improvements in PA and adjacent downwind regions. In addition, comparing across the six scenarios evaluated in this study, vulnerable populations─in both PA and Rest of PJM─benefit most in scenarios that prioritize plant closures near Environmental Justice Areas in PA. These results demonstrate the importance of considering cross-regional linkages and sociodemographics in designing equitable retirement strategies.

Sliding scales for assessing and communicating human and ecological risks and complexities for restoration, remediation crises, and decisions.

Many lands were degraded or destroyed by human activities, including contamination from industry and military facilities. The United States and other industrialized counties have legacy wastes remaining from the Second World War, the Cold War, and industrialization. There is increasing need to return degraded land to suitable future land uses, including ecological parks and preserves. This paper proposes a conceptual model of the different levels of information needed to understand the risk to human health, the environment, and ecological resources. I propose a four-part approach: 1) general model for assessing ecological resources, 2) model for assessment needed for remediation or restoration projects, 3) a sliding scale, conceptual model for causes, events, and sources that lead to exposure and risk, and 4) an additional step that includes environmental justice (equity, diversity and inclusion) as a necessary consideration of traditional exposure assessment. While the factors involved in ecological risk assessment are well established, the combination of human health, ecological health, and environmental justice determining risk for remediation or restoration projects is not. Major factors useful for human health, environmental, and ecological evaluation include causes, events (earthquakes, accidents, chemical releases), sources, exposure, and informational challenges, as well as barriers to exposure. I propose that exposure through an environmental justice (diversity, equity, and inclusion) lens should be a key component of risk assessment. Each of these factors involves a sliding scale or continuum that must be considered in evaluating risk and communicating with the regulators, resource trustees, land managers and the public. The conceptual model also serves as a template for obtaining information about the environment that will be useful for communicating the importance of different risk factors. The model was developed for consideration of remediation on Department of Energy lands, it can be applied more broadly to other projects.

Assessing bias in personal exposure estimates when indoor air quality is ignored: A comparison between GPS-enabled mobile air sensor data and stationary outdoor sensor data.

Neglecting indoor air quality in exposure assessments may lead to biased exposure estimates and erroneous conclusions about the health impacts of exposure and environmental health disparities. This study assessed these biases by comparing two types of personal exposure estimates for 100 individuals: one derived from real-time particulate matter (PM2.5) measurements collected both indoors and outdoors using a low-cost portable air monitor (GeoAir2.0) and the other from PurpleAir sensor network data collected exclusively outdoors. The PurpleAir measurement data were used to create smooth air pollution surfaces using geostatistical methods. To obtain mobility-based exposure estimates, both sets of air pollution data were combined with the individuals' GPS tracking data. Paired-sample t-tests were then performed to examine the differences between these two estimates. This study also investigated whether GeoAir2.0- and PurpleAir-based estimates yielded consistent conclusions about gender and economic disparities in exposure by performing Welch's t-tests and ANOVAs and comparing their t-values and F-values. The study revealed significant discrepancies between GeoAir2.0- and PurpleAir-based estimates, with PurpleAir data consistently overestimating exposure (t = 5.94; p < 0.001). It also found that females displayed a higher average exposure than males (15.65 versus. 8.55 µg/m3) according to GeoAir2.0 data (t = 4.654; p = 0.055), potentially due to greater time spent indoors engaging in pollution-generating activities traditionally associated with females, such as cooking. This contrasted with the PurpleAir data, which indicated higher exposure for males (43.78 versus. 46.26 µg/m3) (t = 3.793; p = 0.821). Additionally, GeoAir2.0 data revealed significant economic disparities (F = 7.512; p < 0.002), with lower-income groups experiencing higher exposure-a disparity not captured by PurpleAir data (F = 0.756; p < 0.474). These findings highlight the importance of considering both indoor and outdoor air quality to reduce bias in exposure estimates and more accurately represent environmental disparities.

Capturing Exposure Disparities with Chemical Transport Models: Evaluating the Suitability of Downscaling Using Land Use Regression.

High resolution exposure surfaces are essential to capture disparities in exposure to traffic-related air pollution in urban areas. In this study, we develop an approach to downscale Chemical Transport Model (CTM) simulations to a hyperlocal level (∼100m) in the Greater Toronto Area (GTA) under three scenarios where emissions from cars, trucks and buses are zeroed out, thus capturing the burden of each transportation mode. This proposed approach statistically fuses CTMs with Land-Use Regression using machine learning techniques. With this proposed downscaling approach, changes in air pollutant concentrations under different scenarios are appropriately captured by downscaling factors that are trained to reflect the spatial distribution of emission reductions. Our validation analysis shows that high-resolution models resulted in better performance than coarse models when compared with observations at reference stations. We used this downscaling approach to assess disparities in exposure to nitrogen dioxide (NO2) for populations composed of renters, low-income households, recent immigrants, and visible minorities. Individuals in all four categories were disproportionately exposed to the burden of cars, trucks, and buses. We conducted this analysis at spatial resolutions of 12, 4, 1 km, and 100 m and observed that disparities were significantly underestimated when using coarse spatial resolutions. This reinforces the need for high-spatial resolution exposure surfaces for environmental justice analyses.

The Clinical, Mechanistic, and Social Impacts of Air Pollution on Atopic Dermatitis.

Atopic dermatitis (AD) is a complex disease characterized by dry, pruritic skin and significant atopic and psychological sequelae. Although AD has always been viewed as multifactorial, early research was dominated by overlapping genetic determinist views of either innate barrier defects leading to inflammation or innate inflammation eroding skin barrier function. However, the incidence of AD in the US has increased since 1970 at a pace that far exceeds genetic drift and thus suggests a modern, environmental etiology. Another implicated factor is Staphylococcus aureus; however, a highly contagious microorganism is unlikely to be the primary etiology of a non-communicable disease. Recently, the roles of the skin and gut microbiomes have received greater attention as potentially targetable drivers of AD. Here too however, dysbiosis on a population scale would require induction by an environmental factor. In this review, we describe the evidence supporting the environmental hypothesis of AD etiology and detail the molecular mechanisms of each AD-relevant toxins. We also outline how a pollution focused paradigm demands earnest engagement with environmental injustice if the field is to meaningfully address racial and geographic disparities. Identifying specific toxins and their mechanisms can also inform in-home and national mitigation strategies.

Decomposition analysis to assess intervention strategies for reducing health-related exposure disparities in Michigan public drinking water systems.

OBJECTIVE: Contamination in U.S. public drinking water systems (PWS) is estimated to cause millions of illnesses and billions of dollars in medical expenditures annually. Few prior studies have explored intervention strategies, including environmental enforcement, to reduce estimated health-related exposure disparities (exposure disparity) in PWS, which are driven partially by socioeconomic status (SES), racism, and PWS characteristics. METHOD: This study used a longitudinal measurement method to estimate the annual health-related exposure level (health level) of each PWS in Michigan, based on data from the Enforcement and Compliance Online (ECHO) and U.S. Census Bureau databases. Using a decomposition model with four strategies, we analyzed how eliminating disparities in SES, proportion minority, environmental enforcement, and PWS characteristics across communities would affect adjusted exposure disparities. RESULTS: This study found that adjusted race- and poverty-based exposure disparities have existed since the 1980s but might have decreased in the last one or two decades. PWS characteristics strongly impacted the crude and adjusted exposure disparity. Environmental enforcement, although less effective in minority-concentrated communities, reduced the adjusted race-based exposure disparity by 10%-20% in the 1980s, 8% in the 1990s, and 0.012% in the 2010s. Equalizing the poverty rate distribution reduced the adjusted race-based exposure disparity by 0.72% in the 1980s and 6.8% in the 2010s. However, equalizing racial and ethnic composition distribution increased the adjusted poverty-based exposure disparity in the 2000s. CONCLUSION: These findings indicate that economically disadvantaged or minority-concentrated communities in Michigan disproportionately suffer from poorer PWS quality. Enhanced environmental enforcement, increased household income, PWS investment, and other actions are needed to address these exposure disparities effectively.

A comparison of population-level exposure and equity tradeoffs across strategies to reduce fine particulate matter emissions from transportation sources in the northeastern US.

BACKGROUND: Many climate mitigation policies to reduce transportation emissions have public health benefits related to ambient air pollution. However, few health analyses consider the equity implications of alternative policies. Equity can be conceptualized in many different ways that may be relevant to communities, decision-makers, and other stakeholders. OBJECTIVES: To evaluate alternative transportation emissions reduction scenarios across the northeastern United States considering population exposure reductions and multiple equity constructs. METHODS: We developed four quantitative indicators reflecting equity constructs that aligned with stakeholder perspectives, including racial/ethnic exposure inequities, proportion of benefits in environmental justice communities, distribution of benefits among participating states, and rural/urban share of benefits. We analyzed numerous transportation emissions reduction scenarios for directly emitted fine particulate matter (primary PM2.5) covering 12 Northeast states and the District of Columbia. We used the Community Multiscale Air Quality model with the decoupled direct method to estimate the reduction in population-weighted primary PM2.5 exposure and the impact on equity for each scenario. RESULTS: Scenarios that yielded greater reductions in population-weighted primary PM2.5 exposure generally emphasized emissions reductions in urban areas or states with large urban centers, with a more than threefold difference in benefits across scenarios. The higher exposure-benefit scenarios typically also had greater reductions in racial/ethnic exposure inequities but led to higher between-state or rural/urban inequality. Scenarios that targeted uniform percentage emission reductions from light or heavy-duty trucks best addressed rural/urban inequalities but led to the smallest reductions in racial/ethnic inequity. CONCLUSION: There are intrinsic tradeoffs among equity constructs, where focusing resources on distributing benefits across states or between urban and rural populations could come at the expense of less reduction in racial/ethnic exposure inequities or in environmental justice communities. Future health benefits analyses should incorporate multiple equity indicators that reflect different stakeholder perspectives and articulate the underlying constructs and tradeoffs.

Design Insights for Industrial CO2 Capture, Transport, and Storage Systems.

We present methods and insights for the design of CO2 capture, transport, and storage systems for industrial facilities with a case study focus on Louisiana. Our analytical framework includes (1) evaluating the scale and concentration of capturable CO2 emissions at individual facilities for the purpose of estimating the cost of CO2 capture retrofits that utilize various energy supply sources to meet parasitic demands; (2) screening to identify potential CO2 storage sites and estimate their capacities, injectivities, and costs; and (3) designing cost-minimized trucking or pipeline infrastructure connecting CO2 capture plants with storage sites, considering existing land uses, demographics, and a variety of social and environmental justice factors. Estimated levelized costs of capture at Louisiana's 190 industrial facilities range from below $50/tCO2 to above $500/tCO2, depending on facility-specific features. We identified 98 potential storage sites with storage costs ranging from $8 to $17/tCO2. We find that in most situations, pipelines are the least-costly mode of CO2 transport. When industrial facilities in a region share pipelines, aggregate pipeline mileage and average transport costs are dramatically lower than without sharing. Shared pipeline networks designed to avoid disadvantaged communities require right-of-way areas compared to those for networks that transect such communities, but result in 25% higher average per-tonne transport cost.

Exploring the feasibility of linking historical air pollution data to the Christchurch Health and Development study: A birth cohort study in Aotearoa, New Zealand.

Spatial life course epidemiological approaches offer promise for prospectively examining the impacts of air pollution exposure on longer-term health outcomes, but existing research is limited. An essential aspect, often overlooked is the comprehensiveness of exposure data across the lifecourse. The primary objective was to meticulously reconstruct historical estimates of air pollution exposure to include prenatal exposure as well as annual exposure from birth to 10 years (1977-1987) for each cohort member. We linked these data from a birth cohort of 1,265 individuals, born in Aotearoa/New Zealand in mid-1977 and studied to age 40, to historical air pollution data to create estimates of exposure from birth to 10 years (1977-1987). Improvements in air quality over time were found. However, outcomes varied by demographic and socioeconomic factors. Future research should examine how inequitable air pollution exposure is related to health outcomes over the life course.

Qualitative and mixed methods: informing and enhancing exposure science.

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.

Using geographic effect measure modification to examine socioeconomic-related surface temperature disparities in New York City.

BACKGROUND: Lower socioeconomic (SES) communities are more likely to be situated in urban heat islands and have higher heat exposures than their higher SES counterparts, and this inequality is expected to intensify due to climate change. OBJECTIVES: To examine the relationship between surface temperatures and SES in New York City (NYC) by employing a novel analytical approach. Through incorporating modifiable features, this study aims to identify potential locations where mitigation interventions can be implemented to reduce heat disparities associated with SES. METHODS: Using the 2013-2017 American Community Survey, U.S Landsat-8 Analysis Ready Data surface temperatures (measured on 8/12/2016), and the NYC Land Cover Dataset at the census tract level (2098 tracts), this study examines the association between two components of tract-level SES (percentage of individuals living below the poverty line and the percentage of individuals without a high school degree) and summer day surface temperature in NYC. First, we examine this association with an unrestricted NYC linear regression, examining the city-wide association between the two SES facets and summer surface temperature, with additional models adjusting for altitude, shoreline, and nature-cover. Then, we assess geographic effect measure modification by employing the same models to three supplemental regression model strategies (borough-restricted and community district-restricted linear regressions, and geographically weighted regression (GWR)) that examined associations within smaller intra-city areas. RESULTS: All regression strategies identified areas where lower neighborhood SES composition is associated with higher summer day surface temperatures. The unrestricted NYC regressions revealed widespread disparities, while the borough-restricted and community district-restricted regressions identified specific political boundaries within which these disparities existed. The GWR, addressing spatial autocorrelation, identified significant socioeconomic heat disparities in locations such as northwest Bronx, central Brooklyn, and uptown Manhattan. These findings underscore the need for targeted policies and community interventions, including equitable urban planning and cooling strategies, to mitigate heat exposure in vulnerable neighborhoods. IMPACT STATEMENT: This study redefines previous research on urban socioeconomic disparities in heat exposure by investigating both modifiable (nature cover) and non-modifiable (altitude and shoreline) built environment factors affecting local temperatures at the census tract level in New York City. Through a novel analytical approach, the research aims to highlight intervention opportunities to mitigate heat disparities related to socioeconomic status. By examining the association between surface temperatures and socioeconomic status, as well as investigating different geographic and governmental scales, this study offers actionable insights for policymakers and community members to address heat exposure inequalities effectively across different administrative boundaries. The objective is to pinpoint potential sites for reducing socioeconomic heat exposure disparities at various geographic and political levels.

Exposure to agricultural pesticides and wheezing among 5-12-year-old children in the Imperial Valley, CA, USA.

Background: Exposure to pesticides has been linked to adverse respiratory health outcomes in children. Methods: We leveraged the Children's Assessing Imperial Valley Respiratory Health and the Environment cohort located in the rural community of Imperial Valley near the US-Mexico border. We calculated the kilograms of total pesticides applied within 400 m of children's residential addresses for the years 2016-2020. Estimated pesticide usage near homes was categorized into three groups (none vs. low vs. high [split at the median]). All health variables (i.e., asthma status and wheezing) were derived from a parent-reported questionnaire on respiratory health. We used generalized linear models, controlling for child sex, the language of survey, health insurance, respondents' highest education, and exposure to environmental secondhand smoking, to calculate prevalence differences between none versus low and high exposure to agricultural pesticides. Results: Approximately 62% of the 708 children (aged 5-12 years) lived within 400 m of at least one pesticide application within 12 months prior to survey administration. Exposure to pesticides within 400 m of children's residences was associated with 12-month prior wheeze. Those in the "high" exposure group had a prevalence of wheezing that was 10 (95% confidence interval: 2%, 17%) percentage points higher than among children not exposed to pesticide applications. Associations for high exposure to specific categories of pesticide applications, sulfur only, all pesticides except sulfur, chlorpyrifos, and glyphosate, also were observed with a higher prevalence of wheezing than among children not exposed to pesticide applications. Conclusions: We observed associations between living near pesticide applications and more wheeze symptoms among children.

Sociodemographic inequalities in residential nighttime light pollution in urban Bulgaria: An environmental justice analysis.

INTRODUCTION: Outdoor nighttime light (NTL) is a potential anthropogenic stressor in urban settings. While ecological studies have identified outdoor NTL exposure disparities, uncertainties remain about disparities in individual exposure levels, particularly in Europe. AIM: To assess whether some populations are disproportionately affected by outdoor NTL at their residences in urban Bulgaria. METHODS: We analyzed 2023 data from a representative cross-sectional survey of 4,270 adults from the five largest Bulgarian cities. Respondents' annual exposures to outdoor artificial nighttime luminance were measured using satellite imagery and assigned at their places of residence. We calculated the Gini coefficient as a descriptive NTL inequality measure. Associations between respondents' NTL exposure levels and sociodemographic characteristics were assessed by estimating quantile mixed regression models. Stratified regressions were fitted by gender and for each city. RESULTS: We found moderate distributive NTL inequalities, as indicated by a 0.214 Gini coefficient. Regression analyses found associations between greater NTL exposure and higher educational attainment. Respondents with incomes perceived as moderate experienced less NTL exposure at the 0.5 and 0.8 quantiles, while unemployed respondents experienced lower exposure at the 0.2 and 0.5 quantiles. We observed null associations for the elderly and non-Bulgarian ethnicities. Regardless of the quantile, greater population density was associated with higher NTL levels. Stratification by sex did not yield substantial differences in the associations. We observed notable city-specific heterogeneities in the associations, with differences in the magnitudes and directions of the associations and the NTL quantiles. CONCLUSIONS: NTL exposures appeared to embody an environmental injustice dimension in Bulgaria. Our findings suggest that some sociodemographic populations experience higher exposure levels to NTL; however, those are not necessarily the underprivileged or marginalized. Identifying populations with high exposure levels is critical to influencing lighting policies to ease related health implications.

Disparities in exposure to concentrated animal feeding operations (CAFOs) and risk of adverse birth outcomes in Pennsylvania, USA.

Background: Previous studies have linked exposure to concentrated animal feeding operations (CAFOs) with various health outcomes. However, relatively few studies evaluated the impacts of CAFOs on adverse birth outcomes, despite significant public health concerns regarding maternal and child health. Objectives: This cross-sectional study investigated the risk of adverse birth outcomes associated with CAFOs exposure and evaluated disparities in exposure to CAFOs and associated health outcomes. Methods: We obtained individual-level birth records from 2003 to 2020 from the Pennsylvania Department of Health. We considered two adverse birth outcomes: (1) preterm birth (PTB); and (2) low birth weight (LBW). Exposure was considered as a binary indicator (presence or absence of CAFO) and as categories based on level of exposure. Logistic regression was applied to estimate the association between CAFOs exposure and adverse birth outcomes. Models were adjusted for infant's sex, maternal demographics (age, race/ethnicity, education), prenatal BMI, prenatal care, smoking status, marital status, plurality, WIC status, and urban/rural indicator. We examined both disparities in exposure and in health response. Results: Presence of CAFOs was associated with higher risk of PTB, with an increasing trend with higher levels of CAFOs exposure. Compared to the no CAFO exposure group, the odds ratios for PTB were 1.022 (95 % confidence interval 1.003, 1.043), 1.066 (1.034, 1.100), 1.069 (1.042, 1.097) for low, medium, and high CAFOs exposure groups, respectively. Some maternal characteristics were associated with a higher CAFO-related risk of PTB. Similar associations were observed for LBW for some characteristics such as mother's race/ethnicity, education, WIC status, and urbanicity, although some findings were not statistically significant. Conclusions: Our findings suggest that presence of CAFOs increases risk of preterm birth. Our results indicate that some maternal characteristics may be associated with higher risk of CAFO-related PTB or LBW. This study can inform future research on disparities in CAFO exposure and associated health burden.

The Association of Socio-Environmental Inequality and Outcomes Among Patients Undergoing Major Surgery.

INTRODUCTION: Environmental hazards may influence health outcomes and be a driver of health inequalities. We sought to characterize the extent to which social-environmental inequalities were associated with surgical outcomes following a complex operation. METHODS: In this cross-sectional study, patients who underwent abdominal aortic aneurysm repair, coronary artery bypass grafting, colectomy, pneumonectomy, or pancreatectomy between 2016 and 2021 were identified from Medicare claims data. Patient data were linked with social-environmental data sourced from Centers for Disease Control and Agency for Toxic Substances and Disease Registry data based on county of residence. The Environmental Justice Index social-environmental ranking (SER) was used as a measure of environmental injustice. Multivariable regression analysis was performed to assess the relationship between SER and surgical outcomes. RESULTS: Among 1,052,040 Medicare beneficiaries, 346,410 (32.9%) individuals lived in counties with low SER, while 357,564 (33.9%) lived in counties with high SER. Patients experiencing greater social-environmental injustice were less likely to achieve textbook outcome (odds ratio 0.95, 95% confidence interval 0.94-0.96, P < 0.001) and to be discharged to an intermediate care facility or home with a health agency (odds ratio 0.97, 95% confidence interval 0.96-0.98, P < 0.001). CONCLUSIONS: Cumulative social and environmental inequalities, as captured by the Environmental Justice Index SER, were associated with postoperative outcomes among Medicare beneficiaries undergoing a range of surgical procedures. Policy makers should focus on environmental, as well as socioeconomic injustice to address preventable health disparities.

Drinking water source and exposure to regulated water contaminants in the California Teachers Study cohort.

BACKGROUND: Pollutants including metals/metalloids, nitrate, disinfection byproducts, and volatile organic compounds contaminate federally regulated community water systems (CWS) and unregulated domestic wells across the United States. Exposures and associated health effects, particularly at levels below regulatory limits, are understudied. OBJECTIVE: We described drinking water sources and exposures for the California Teachers Study (CTS), a prospective cohort of female California teachers and administrators. METHODS: Participants' geocoded addresses at enrollment (1995-1996) were linked to CWS service area boundaries and monitoring data (N = 115,206, 92%); we computed average (1990-2015) concentrations of arsenic, uranium, nitrate, gross alpha (GA), five haloacetic acids (HAA5), total trihalomethanes (TTHM), trichloroethylene (TCE), and tetrachloroethylene (PCE). We used generalized linear regression to estimate geometric mean ratios of CWS exposures across demographic subgroups and neighborhood characteristics. Self-reported drinking water source and consumption at follow-up (2017-2019) were also described. RESULTS: Medians (interquartile ranges) of average concentrations of all contaminants were below regulatory limits: arsenic: 1.03 (0.54,1.71) µg/L, uranium: 3.48 (1.01,6.18) µg/L, GA: 2.21 (1.32,3.67) pCi/L, nitrate: 0.54 (0.20,1.97) mg/L, HAA5: 8.67 (2.98,14.70) µg/L, and TTHM: 12.86 (4.58,21.95) µg/L. Among those who lived within a CWS boundary and self-reported drinking water information (2017-2019), approximately 74% self-reported their water source as municipal, 15% bottled, 2% private well, 4% other, and 5% did not know/missing. Spatially linked water source was largely consistent with self-reported source at follow-up (2017-2019). Relative to non-Hispanic white participants, average arsenic, uranium, GA, and nitrate concentrations were higher for Black, Hispanic and Native American participants. Relative to participants living in census block groups in the lowest socioeconomic status (SES) quartile, participants in higher SES quartiles had lower arsenic/uranium/GA/nitrate, and higher HAA5/TTHM. Non-metropolitan participants had higher arsenic/uranium/nitrate, and metropolitan participants had higher HAA5/TTHM. IMPACT: Though average water contaminant levels were mostly below regulatory limits in this large cohort of California women, we observed heterogeneity in exposures across sociodemographic subgroups and neighborhood characteristics. These data will be used to support future assessments of drinking water exposures and disease risk.

A systematic review of animal feeding operations including concentrated animal feeding operations (CAFOs) for exposure, health outcomes, and environmental justice.

BACKGROUND: Despite growing literature on animal feeding operations (AFOs) including concentrated animal feeding operations (CAFOs), research on disproportionate exposure and associated health burden is relatively limited and shows inconclusive findings. OBJECTIVE: We systematically reviewed previous literature on AFOs/CAFOs, focusing on exposure assessment, associated health outcomes, and variables related to environmental justice (EJ) and potentially vulnerable populations. METHODS: We conducted a systematic search of databases (MEDLINE/PubMed and Web of Science) and performed citation screening. Screening of titles, abstracts, and full-text articles and data extraction were performed independently by pairs of reviewers. We summarized information for each study (i.e., study location, study period, study population, study type, study design, statistical methods, and adjusted variables (if health association was examined), and main findings), AFO/CAFO characteristics and exposure assessment (i.e., animal type, data source, measure of exposure, and exposure assessment), health outcomes or symptoms (if health association was examined), and information related to EJ and potentially vulnerable populations (in relation to exposure and/or health associations, vulnerable populations considered, related variables, and main findings in relation to EJ and vulnerable populations). RESULTS: After initial screening of 10,963 papers, we identified 76 eligible studies. This review found that a relatively small number of studies (20 studies) investigated EJ and vulnerability issues related to AFOs/CAFOs exposure and/or associated health outcomes (e.g., respiratory diseases/symptoms, infections). We found differences in findings across studies, populations, the metrics used for AFO/CAFO exposure assessment, and variables related to EJ and vulnerability. The most commonly used metric for AFO/CAFO exposure assessment was presence of or proximity to facilities or animals. The most investigated variables related to disparities were race/ethnicity and socioeconomic status. CONCLUSION: Findings from this review provide suggestive evidence that disparities exist with some subpopulations having higher exposure and/or health response in relation to AFO/CAFO exposure, although results varied across studies.

Enhancing Human Health and Wellbeing through Sustainably and Equitably Unlocking a Healthy Ocean's Potential.

A healthy ocean is essential for human health, and yet the links between the ocean and human health are often overlooked. By providing new medicines, technologies, energy, foods, recreation, and inspiration, the ocean has the potential to enhance human health and wellbeing. However, climate change, pollution, biodiversity loss, and inequity threaten both ocean and human health. Sustainable realisation of the ocean's health benefits will require overcoming these challenges through equitable partnerships, enforcement of laws and treaties, robust monitoring, and use of metrics that assess both the ocean's natural capital and human wellbeing. Achieving this will require an explicit focus on human rights, equity, sustainability, and social justice. In addition to highlighting the potential unique role of the healthcare sector, we offer science-based recommendations to protect both ocean health and human health, and we highlight the unique potential of the healthcare sector tolead this effort.