THE LONG-TERM DYNAMICS OF RACIAL/ETHNIC INEQUALITY IN NEIGHBORHOOD AIR POLLUTION EXPOSURE, 1990-2009

PM2.5 exposure and household income are associated with lung function abnormalities in children with sickle cell disease

RATIONALE

Cardiopulmonary dysfunction is a major contributor to mortality among persons with sickle cell disease (pwSCD). Despite this, little is known regarding environmental drivers of lung function decline.

OBJECTIVE

We hypothesized that environmental and socioeconomic variables have a significant effect on lung function in pwSCD that can be detected by spirometry.

METHODS

We retrospectively analyzed all spirometry results from pwSCD followed in the Pediatric Pulmonology clinic at the Children's Hospital of Philadelphia since 1 January 2016.

RESULTS

The study included 349 spirometry tests from 128 patients, primarily "Black or African American" (88%) and male (61%). More frequent exposure to PM2.5 above 25 μg/m3 was associated with higher odds of obstruction. Specifically, when compared to incidence of exposure to PM2.5 above 25 μg/m3 <25th percentile, both pwSCD exposed to 25th-75th percentile and pwSCD >75th percentile had higher odds of obstruction on spirometry (25th-75th: odds ratio [OR]: 9.6, p = .017; >75th: OR: 31.85, p = .002) despite correction for potential confounders. Similarly, median household income below the mean was associated with higher odds of restriction (OR: 4.37; p = .009).

CONCLUSIONS

We report higher odds of obstruction in pwSCD frequently exposed to PM2.5 concentrations above 25 μg/m3 and higher odds of restriction in pwSCD with lower household income. Our findings link spirometry patterns to modifiable risk factors indicating that there may opportunities for early intervention in pwSCD that have been referred to a pulmonology clinic. Further research is needed to assess if these findings can be generalized to the wider population of pwSCD.

GWAS reveals Genetic Susceptibility to Air Pollution-Related Asthma Exacerbations in Children of African Ancestry

Background

The relationship between ambient air pollution (AAP) exposure and asthma exacerbations is well-established. However, mitigation efforts have yielded mixed results, potentially due to genetic variability in the response to AAP. We hypothesize that common single nucleotide polymorphisms (SNPs) are linked to AAP sensitivity and test this through a Genome Wide Association Study (GWAS).

Methods

We selected a cohort of pediatric asthma patients frequently exposed to AAP. Patients experiencing exacerbations immediately following AAP spikes were deemed sensitive. A GWAS compared sensitive versus non-sensitive patients. Findings were validated using data from the All of Us program.

Results

Our study included 6,023 pediatric asthma patients. Due to the association between AAP exposure and race, GWAS analysis was feasible only in the African ancestry cohort. Seven risk loci reached genome-wide significance, including four non-intergenic variants. Two variants were validated: rs111970601 associated with sensitivity to CO (odds ratio [OR], 6.58; PL=L1.63L×L10-8; 95% CI, 3.42-12.66) and rs9836522 to PM2.5 sensitivity (OR 0.75; PL=L3,87 ×L10-9; 95% CI, 0.62-0.91).

Interpretation

While genetic variants have been previously linked to asthma incidence and AAP exposure, this study is the first to link specific SNPs with AAP-related asthma exacerbations. The identified variants implicate genes with a known role in asthma and established links to AAP. Future research should explore how clinical interventions interact with genetic risk to mitigate the effects of AAP, particularly to enhance health equity for vulnerable populations.

What is already known on this topic

The relationship between ambient air pollution (AAP) exposure and asthma exacerbations is well-established. However, efforts to mitigate the impact of AAP on children with asthma have yielded mixed results, potentially due to genetic variability in response to AAP.

What this study adds

Using publicly available AAP data, we identify which children with asthma experience exacerbations immediately following spikes in AAP. We then conduct a Genome Wide Association Study (GWAS) comparing these patients with those who have no temporal association between AAP spikes and asthma exacerbations, identifying several Single Nucleotide Polymorphisms (SNPs) significantly associated with AAP sensitivity.

How this study might affect research practice or policy

While genetic variants have previously been linked to asthma incidence and AAP exposure, this study is the first to link specific SNPs with AAP-related asthma exacerbations. This creates a framework for identifying children especially at risk when exposed to AAP. These children should be targeted with policy interventions to reduce exposure and may require specific treatments to mitigate the effects of ongoing AAP exposure in the interim.

Social and Behavior Factors of Alzheimer's Disease and Related Dementias: A National Study in the U.S

INTRODUCTION

Considerable research has linked many risk factors to Alzheimer's Disease and Related Dementias (ADRD). Without a clear etiology of ADRD, it is advantageous to rank the known risk factors by their importance and determine if disparities exist. Statistical-based ranking can provide insight into which risk factors should be further evaluated.

METHODS

This observational, population-based study assessed 50 county-level measures and estimates related to ADRD in 3,155 counties in the U.S. using data from 2010 to 2021. Statistical analysis was performed in 2022-2023. The machine learning method, eXtreme Gradient Boosting, was utilized to rank the importance of these variables by their relative contribution to the model performance. Stratified ranking was also performed based on a county's level of disadvantage. Shapley Additive exPlanations (SHAP) provided marginal contributions for each variable.

RESULTS

The top three ranked predictors at the county level were insufficient sleep, consuming less than one serving of fruits/vegetables per day among adults, and having less than a high school diploma. In both disadvantaged and non-disadvantaged counties, demographic variables such as sex and race were important in predicting ADRD. Lifestyle factors ranked highly in non-disadvantaged counties compared to more environmental factors in disadvantaged counties.

CONCLUSIONS

This ranked list of factors can provide a guided approach to ADRD primary prevention strategies in the U.S., as the effects of sleep, diet, and education on ADRD can be further developed. While sleep, diet, and education are important nationally, differing prevention strategies could be employed based on a county's level of disadvantage.

Gentrification Yields Racial And Ethnic Disparities In Exposure To Contextual Determinants Of Health

This article examines racial and ethnic disparities in the relationship between gentrification and exposure to contextual determinants of health. In our study, we focused on changes in selected contextual determinants of health (health care access, social deprivation, air pollution, and walkability) and life expectancy during the period 2006-21 among residents of gentrifying census tracts in six large US cities that have experienced different gentrification patterns and have different levels of segregation: Chicago, Illinois; Los Angeles, California; New York, New York; Philadelphia, Pennsylvania; San Francisco, California; and Seattle, Washington. We found that gentrification was associated with overall improvements in the likelihood of living in Medically Underserved Areas across racial and ethnic groups, but it was also associated with increased social deprivation and reduced life expectancy among Black people, Hispanic people, and people of another or undetermined race or ethnicity. In contrast, we found that gentrification was related to better (or unchanged) contextual determinants of health for Asian people and White people. Our findings can inform policies that target communities identified to be particularly at risk for worsening contextual determinants of health as a result of gentrification.

Air Pollution and Racial Disparities in Pregnancy Outcomes in the United States: A Systematic Review

BACKGROUND

Exposure to air pollutants and other environmental factors increases the risk of adverse pregnancy outcomes. There is growing evidence that adverse outcomes related to air pollution disproportionately affect racial and ethnic minorities. The objective of this paper is to explore the importance of race as a risk factor for air pollution-related poor pregnancy outcomes.

METHODS

Studies investigating the effects of exposure to air pollution on pregnancy outcomes by race were reviewed. A manual search was conducted to identify missing studies. Studies that did not compare pregnancy outcomes among two or more racial groups were excluded. Pregnancy outcomes included preterm births, small for gestational age, low birth weight, and stillbirths.

RESULTS

A total of 124 articles explored race and air pollution as risk factors for poor pregnancy outcome. Thirteen percent of these (n=16) specifically compared pregnancy outcomes among two or more racial groups. Findings across all reviewed articles showed more adverse pregnancy outcomes (preterm birth, small for gestational age, low birth weight, and stillbirths) related to exposure to air pollution among Blacks and Hispanics than among non-Hispanic Whites.

CONCLUSION

Evidence support our general understanding of the impact of air pollution on birth outcomes and, specifically, of disparities in exposure to air pollution and birth outcomes for infants born to Black and Hispanic mothers. The factors driving these disparities are multifactorial, mostly social, and economic factors. Reducing or eliminating these disparities require interventions at individual, community, state, and national level.

Ambient Air Pollution and Outpatient Morbidities in Bronchopulmonary Dysplasia

Rationale: Bronchopulmonary dysplasia (BPD) is the most common long-term complication of prematurity. Although socioeconomic status is associated with BPD morbidities, the drivers of this association are poorly understood. In the United States, ambient air pollution (AAP) exposure is linked to both race/ethnicity and socioeconomic status. Furthermore, AAP exposure is known to have a detrimental effect on respiratory health in children. Objectives: To assess if AAP exposure is linked to BPD morbidity in the outpatient setting. Methods: Participants with BPD were recruited from outpatient clinics at Johns Hopkins University and the Children's Hospital of Philadelphia between 2008 and 2021 (N = 800) and divided into low, moderate, and high AAP exposure groups, based on publicly available U.S. Environmental Protection Agency data. Clinical data were obtained by chart review and caregiver questionnaires. Results: Non-White race, home ventilator use, and lower median household income were associated with higher degrees of air pollution exposure. After adjustment for these factors, moderate and high air pollution exposure were associated with requiring systemic steroids (odds ratio, 1.78 and 2.17, respectively) compared with low air pollution. Similarly, high air pollution exposure was associated with emergency department visits (odds ratio, 1.59). Conclusions: This study demonstrates an association between AAP exposure and BPD morbidity after initial hospital discharge. AAP exposure was closely linked to race and median household income. As such, it supports the notion that AAP exposure may be contributing to health disparities in BPD outcomes. Further studies directly measuring exposure and establishing a link between biomarkers of exposure and outcomes are prerequisites to developing targeted interventions protecting this vulnerable population.

Racial/ethnic disparities in PM2.5-attributable cardiovascular mortality burden in the United States

Average ambient fine particulate matter (PM2.5) concentrations have decreased in the US in recent years, but the health benefits of this improvement among different racial/ethnic groups are unknown. We estimate the associations between long-term exposure to ambient PM2.5 and cause-specific cardiovascular disease (CVD) mortality rate and assess the PM2.5-attributable CVD deaths by race/ethnicity across 3,103 US counties during 2001-2016 (n = 595,776 county-months). A 1 µg m-3 increase in PM2.5 concentration was associated with increases of 7.16 (95% confidence interval (CI): 3.81, 10.51) CVD deaths per 1,000,000 Black people per month, significantly higher than the estimates for non-Hispanic white people (1.76 (95% CI: 1.37, 2.15); difference in coefficients: 5.40 (95% CI: 2.03, 8.77), P = 0.001). No significant difference in this association was observed between Hispanic (2.66 (95% CI: -0.03, 5.35)) and non-Hispanic white people (difference in coefficients: 0.90 (95% CI: -1.81, 3.61), P = 0.523). From 2001 to 2016, the absolute disparity in PM2.5-attributable CVD mortality burden was reduced by 44.04% between non-Hispanic Black and white people and by 2.61% between Hispanic and non-Hispanic white people. However, in 2016, the burden remained 3.47 times higher for non-Hispanic Black people and 0.45 times higher for Hispanic people than for non-Hispanic white people. We call for policies that aim to reduce both exposure and vulnerability to PM2.5 for racial/ethnic minorities.

Pan-cancer mutational signature surveys correlated mutational signature with geospatial environmental exposures and viral infections

Background

Cancer has been disproportionally affecting minorities. Genomic-based cancer disparity analyses have been less common than conventional epidemiological studies. In the past decade, mutational signatures have been established as characteristic footprints of endogenous or exogenous carcinogens.

Methods

Integrating datasets of diverse cancer types from The Cancer Genome Atlas and geospatial environmental risks of the registry hospitals from the United States Environmental Protection Agency, we explored mutational signatures from the aspect of racial disparity concerning pollutant exposures. The raw geospatial environmental exposure data were refined to 449 air pollutants archived and modeled from 2007 to 2017 and aggregated to the census county level. Additionally, hepatitis B and C viruses and human papillomavirus infection statuses were incorporated into analyses for skin cancer, cervical cancer, and liver cancer.

Results

Mutation frequencies of key oncogenic genes varied substantially between different races. These differences were further translated into differences in mutational signatures. Survival analysis revealed that the increased pollution level is associated with worse survival. The analysis of the oncogenic virus revealed that aflatoxin, an affirmed carcinogen for liver cancer, was higher in Asian liver cancer patients than in White patients. The aflatoxin mutational signature was exacerbated by hepatitis infection for Asian patients but not for White patients, suggesting a predisposed genetic or genomic disadvantage for Asians concerning aflatoxin.

Conclusions

Environmental pollutant exposures increase a mutational signature level and worsen cancer prognosis, presenting a definite adverse risk factor for cancer patients.

Effects of Prolonged Exposure to Air Pollution and Neighborhood Disadvantage on Self-Rated Health among Adults in the United States: Evidence from the Panel Study of Income Dynamics

BACKGROUND

Although overall air quality has improved in the United States, air pollution remains unevenly distributed across neighborhoods, producing disproportionate environmental burdens for minoritized and socioeconomically disadvantaged residents for whom greater exposure to other structurally rooted neighborhood stressors is also more frequent. These interrelated dynamics and layered vulnerabilities each have well-documented associations with physical and psychological health outcomes; however, much remains unknown about the joint effects of environmental hazards and neighborhood socioeconomic factors on self-reported health status.

OBJECTIVES

We examined the nexus of air pollution exposure, neighborhood socioeconomic disadvantage, and self-rated health (SRH) among adults in the United States.

METHODS

This observational study used individual-level data from the Panel Study of Income Dynamics merged with contextual information, including neighborhood socioeconomic and air pollution data at the census tract and census block levels, spanning the period of 1999-2015. We estimated ordinary least squares regression models predicting SRH by 10-y average exposures to fine particulate matter [particles ≤ 2.5 μ m in aerodynamic diameter (PM 2.5 )] and neighborhood socioeconomic disadvantage while controlling for individual-level correlates of health. We also investigated the interaction effects of air pollution and neighborhood socioeconomic disadvantage on SRH.

RESULTS

On average, respondents in our sample rated their health as 3.41 on a scale of 1 to 5. Respondents in neighborhoods with higher 10-y average PM 2.5 concentrations or socioeconomic disadvantage rated their health more negatively after controlling for covariates [β = - 0.024 (95% CI: - 0.034 , - 0.014 ); β = - 0.107 (95% CI: - 0.163 , - 0.052 ), respectively]. We also found that the deleterious associations of PM 2.5 exposure with SRH were weaker in the context of greater neighborhood socioeconomic disadvantage (β = 0.007 ; 95% CI: 0.002, 0.011).

DISCUSSION

Study results indicate that the effects of air pollution on SRH may be less salient in socioeconomically disadvantaged neighborhoods compared with more advantaged areas, perhaps owing to the presence of other more proximate structurally rooted health risks and vulnerabilities in disinvested areas (e.g., lack of economic resources, health access, healthy food options). This intersection may further underscore the importance of meaningful involvement and political power building among community stakeholders on issues concerning the nexus of environmental and socioeconomic justice, particularly in structurally marginalized communities. https://doi.org/10.1289/EHP11268.

Environmental Justice: Where It Has Been, and Where It Might Be Going

Taking stock of environmental justice (EJ) is daunting. It is at once a scholarly field, an ongoing social movement, and an administrative imperative adopted by government agencies and incorporated into legislation. Moreover, within academia, it is multidisciplinary and multimethodological, comprising scholars who do not always speak to one another. Any review of EJ is thus necessarily restrictive. This article explores several facets of EJ activism. One is its coalitional and "inside-outside" orientation. EJ activists are constantly forming alliances with other stakeholders, but these coalitions do not flout the importance of engaging with formal institutions. The review next turns to one set of such institutions-the courts and regulatory agencies-to see how well EJ claims have fared there. I then survey scientific findings that have been influenced by EJ. The review concludes with future directions for activists and scholars to consider: the changing nature of EJ coalitions, fragmentation within EJ and with other fields, the historical roots of environmental injustice, and opportunities for stronger infusion of the EJ lens.

Exposure, Susceptibility, and Recovery: A Framework for Examining the Intersection of the Social and Physical Environments and Infectious Disease Risk

Despite well-documented evidence that structurally disadvantaged populations are disproportionately affected by infectious diseases, our understanding of the pathways that connect structural disadvantage to the burden of infectious diseases is limited. We propose a conceptual framework to facilitate more rigorous examination and testing of hypothesized mechanisms through which social and environmental factors shape the burden of infectious diseases and lead to persistent inequities. Drawing upon the principles laid out by Link and Phelan in their landmark paper on social conditions (J Health Soc Behav. 1995;(spec no.):80-94), we offer an explication of potential pathways through which structural disadvantage (e.g., racism, sexism, and economic deprivation) operates to produce infectious disease inequities. Specifically, we describe how the social environment affects an individual's risk of infectious disease by 1) increasing exposure to infectious pathogens and 2) increasing susceptibility to infection. This framework will facilitate both the systematic examination of the ways in which structural disadvantage shapes the burden of infectious disease and the design of interventions that can disrupt these pathways.

Multiscale Analysis of the Relationship between Toxic Chemical Hazard Risks and Racial/Ethnic and Socioeconomic Groups in Texas, USA

Although quantitative environmental (in)justice research demonstrates a disproportionate burden of toxic chemical hazard risks among racial/ethnic minorities and people in low socioeconomic positions, limited knowledge exists on how racial/ethnic and socioeconomic groups across geographic spaces experience toxic chemical hazards. This study analyzed the spatial non-stationarity in the associations between toxic chemical hazard risk and community characteristics of census block groups in Texas, USA, for 2017 using a multiscale geographically weighted regression. The results showed that the percentage of Black or Asian population has significant positive associations with toxic risk across block groups in Texas, meaning that racial minorities suffered more from toxic risk wherever they are located in the state. By contrast, the percentage of Hispanic or Latino has a positive relationship with toxic risk, and the relationship varies locally and is only significant in eastern areas of Texas. Statistical associations between toxic risk and socioeconomic variables are not stationary across the state, showing sub-state patterns of spatial variation in terms of the sign, significant level, and magnitude of the coefficient. Income has a significant negative association with toxic risk around the Dallas-Fort Worth-Arlington Metropolitan Statistical Area. Proportions of people without high school diploma and the unemployment rate both have positive relationships with toxic risk in the eastern area of Texas. Our findings highlight the importance of identifying the spatial patterns of the association between toxic chemical hazard risks and community characteristics at the census block group level for addressing environmental inequality.

Inequities in ambient fine particulate matter: A spatiotemporal analysis in Canadian communities

BACKGROUND

Exposure to fine particulate matter (PM_2.5) is associated with adverse health outcomes but communities are not randomly exposed to PM_2.5. Previous cross-sectional environmental injustice analyses in Canada found disproportionately higher exposure to PM_2.5 in low-income populations, visible minorities and immigrants. Beyond static surveillance, it is also important to evaluate how changes in PM_2.5 exposure over time may differentially impact disadvantaged communities. We examine whether communities with different sociodemographic characteristics benefited equitably from the overall decreases in ambient concentrations of PM_2.5 from 2001 to 2016 in Canada.

METHODS

We derived census tract level estimates of average annual PM_2.5 using validated satellite-based estimations of annual average PM_2.5 concentration surfaces. We investigated how the spatial distribution of PM_2.5 has evolved over 15 years (2001-2016) by comparing absolute values and rank percentiles of census tract level annual average PM_2.5 concentrations in 2001 and 2016. Using decennial census data and multivariable linear regression, we determined if sociodemographic characteristics are associated with changes in exposure to PM_2.5, accounting for geographic boundary changes between census periods.

RESULTS

Overall, ambient PM_2.5 concentrations decreased from 2001 (median of 9.1 μg/m³) to 2016 (median of 6.4 μg/m³), with varying provincial patterns. Across communities, ranked census tract specific PM_2.5 in 2001 and in 2016 are highly correlated (Spearman's rho = 0.75). We found that, on average and accounting for provincial differences and baseline PM_2.5, communities with greater density of aboriginal population, lower education, higher shelter-cost-to-income ratio, unemployment or lower income experienced smaller absolute decreases in PM_2.5 from 2001 to 2016.

CONCLUSIONS

Identifying sociodemographic groups that benefit least from decreasing exposure to PM_2.5 highlights the need to consider environmental injustice when designing or revising air pollution policies.

The effects of the historical practice of residential redlining in the United States on recent temporal trends of air pollution near New York City schools

BACKGROUND

In the 1930's the United States (US) sponsored Home Owners' Loan Corporation (HOLC) created maps that determined risk for mortgage lending based on the racial and ethnic composition of neighborhoods leading to disinvestment in "redlined" or highest risk neighborhoods. This historical practice has perpetuated racial and economic segregation, and health disparities, that persist today. Interventions near schools where children spend large portions of the day, could impact large groups of children but schools are an often-overlooked environment for exposure. Despite a declining trend of ambient pollution in New York City (NYC) between 1998 and 2012, little is known about differences in air quality improvement near schools by historical redlining neighborhood status. Our objective was to examine if recent temporal trends of air pollution near NYC public schools differed in historically redlined neighborhoods.

METHODS

We examined annual average street-level concentrations of combustion-related air pollutants (black carbon (BC), particulate matter (PM_2.5), nitrogen dioxide (NO₂), and nitric oxide (NO)), within a 250-m radius around schools using NYC Community Air Survey land-use regression models (n = 1,462). Year of monitoring, historical redlining (binary), and summer ozone were included in multivariable linear regression using generalized estimating equation models. Average annual percent change (APC) in pollutant concentration was calculated. Models were further stratified by historical redlining and a multiplicative interaction term (year of monitoring × historical redlining) was used to assess effect modification.

RESULTS

Overall, there was a decreasing trend of BC (APC = -4.40%), PM_2.5 (-3.92%), NO₂ (-2.76%), and NO (-6.20%) during the 10-year period. A smaller reduction of BC, PM_2.5 and NO was observed in redlined neighborhoods (n = 722), compared to others (n = 740): BC (APC: -4.11% vs -4.69%; P_interaction < 0.01), PM_2.5 (-3.82% vs -4.11%; P_interaction < 0.01), and NO (-5.73% vs -6.67%; P_interaction < 0.01). Temporal trends of NO₂ did not differ by historical redlining (P_interaction = 0.60).

CONCLUSIONS

Despite significant reductions in annual average pollution concentrations across NYC, schools in historically redlined neighborhoods, compared to others, experienced smaller decrease in pollution, highlighting a potential ongoing ramification of the discriminatory practice.

Associations between long-term exposures to airborne PM2.5 components and mortality in Massachusetts: mixture analysis exploration

BACKGROUND

Numerous studies have documented PM_2.5's links with adverse health outcomes. Comparatively fewer studies have evaluated specific PM_2.5 components. The lack of exposure measurements and high correlation among different PM_2.5 components are two limitations.

METHODS

We applied a novel exposure prediction model to obtain annual Census tract-level concentrations of 15 PM_2.5 components (Zn, V, Si, Pb, Ni, K, Fe, Cu, Ca, Br, SO₄^2-, NO₃^-, NH₄⁺, OC, EC) in Massachusetts from 2000 to 2015, to which we matched geocoded deaths. All non-accidental mortality, cardiovascular mortality, and respiratory mortality were examined for the population aged 18 or over. Weighted quantile sum (WQS) regression models were used to examine the cumulative associations between PM_2.5 components mixture and outcomes and each component's contributions to the cumulative associations. We have fit WQS models on 15 PM_2.5 components and a priori identified source groups (heavy fuel oil combustion, biomass burning, crustal matter, non-tailpipe traffic source, tailpipe traffic source, secondary particles from power plants, secondary particles from agriculture, unclear source) for the 15 PM_2.5 components. Total PM_2.5 mass analysis and single component associations were also conducted through quasi-Poisson regression models.

RESULTS

Positive cumulative associations between the components mixture and all three outcomes were observed from the WQS models. Components with large contribution to the cumulative associations included K, OC, and Fe. Biomass burning, traffic emissions, and secondary particles from power plants were identified as important source contributing to the cumulative associations. Mortality rate ratios for cardiovascular mortality were of greater magnitude than all non-accidental mortality and respiratory mortality, which is also observed in cumulative associations estimated from WQS, total PM_2.5 mass analysis, and single component associations.

CONCLUSION

We have found positive associations between the mixture of 15 PM_2.5 components and all non-accidental mortality, cardiovascular mortality, and respiratory mortality. Among these components, Fe, K, and OC have been identified as having important contribution to the cumulative associations. The WQS results also suggests potential source effects from biomass burning, traffic emissions, and secondary particles from power plants.

How Do Perceived Changes in Child and Adolescent Activities Relate to Perceptions of Health during COVID-19? Exploring Heterogeneity during the Pandemic

COVID-19 affected child/adolescent activities (e.g., extra-curricular, screen time), along with physical health (PH) and mental health (MH); however, less is known about the relationship between changes in activities and PH and MH in the United States and how these relationships vary by race/ethnicity. To address this gap, data were used from a national survey (Socio-Economic Impacts of COVID-19 Survey) administered May-June 2021 (n = 853). Multinomial logistic regression explored changes in outdoor, school, extracurricular, friend, and screen time activities with changes in PH and MH; interactions explored moderation by race/ethnicity. Results showed increases in outdoor (RRR 2.36, p = 0.003), school (RRR 3.07, p < 0.001), and extracurricular activities (RRR 3.05, p < 0.001), which were associated with increases in chances of better PH. Better MH was more likely for children/adolescents where friend activities (RRR 3.34, p < 0.001) and extracurriculars (RRR 4.48, p < 0.001) increased. Except for extracurriculars, heterogeneous relationships were observed (e.g., increases and decreases in activities were simultaneously related to better and worse health). The relationship between outdoor activities and screen time with health were moderated by race/ethnicity. Findings support facilitating outdoor, school, extracurricular, and friend activities, which were positively related to health. Given heterogeneity and variation by race/ethnicity, more research is needed to understand the complex relationship between activities and health during COVID-19.

Gentrification, Mobility, and Exposure to Contextual Social Determinants of Health

This study uses individual level consumer trace data for 2006 residents of low- and moderate-income neighborhoods for the principal cities of the 100 largest metropolitan regions in the US using their location in 2006 and 2019 to examine exposure to the following four cSDOH: healthcare access (Medically Underserved Areas), socioeconomic condition (Area Deprivation Index), air pollution (NO2, PM 2.5 and PM10), and walkability (National Walkability Index). The results control for individual characteristics and initial neighborhood conditions. Residents of neighborhoods classified as gentrifying were exposed to more favorable cSDOH as of 2006 relative to residents of low- and moderate-income neighborhoods that were not gentrifying in terms of likelihood to be in a MUA, and level of local deprivation and walkability while experiencing similar level of air pollution. As a result of changes in neighborhood characteristics and differential mobility pattern, between 2006 and 2019, individuals who originally lived in gentrifying neighborhoods experienced worse changes in MUAs, ADI, and Walkability Index but a greater improvement in exposure to air pollutants. The negative changes are driven by movers, while stayers actually experience a relative improvement in MUAs and ADI and larger improvements in exposure to air pollutants. The findings indicate that gentrification may contribute to health disparities through changes in exposure to cSDOH through mobility to communities with worse cSDOH among residents of gentrifying neighborhoods although results in terms of exposure to health pollutants are mixed.

Neurotoxicants, the Developing Brain, and Mental Health

While life in urban environments may confer a number of benefits, it may also result in a variety of exposures, with toxic consequences for neurodevelopment and neuropsychological health. Neurotoxicants are any of a large number of chemicals or substances that interfere with normal function and/or compromise adaptation in the central and/or peripheral nervous system. Evidence suggests that neurotoxicant effects have a greater effect when occurring in utero and during early childhood. Recent findings exploring neural-level mechanisms provide a crucial opportunity to explore the ways in which environmental conditions may get "under the skin" to impact a number of psychological behaviors and cognitive processes, ultimately allowing for greater synergy between macro- and microlevel efforts to improve mental health in the presence of neurotoxicant exposures. In this review, we provide an overview of 3 types of neurotoxicants related to the built environment and relevant to brain development during childhood and adolescence: lead exposure, outdoor particulate matter pollution, and endocrine-disrupting chemicals. We also discuss mechanisms through which these neurotoxicants affect central nervous system function, including recent evidence from neuroimaging literature. Furthermore, we discuss neurotoxicants and mental health during development in the context of social determinants and how differences in the spatial distribution of neurotoxicant exposures result in health disparities that disproportionately affect low-income and minority populations. Multifaceted approaches incorporating social systems and their effect on neurotoxicant exposures and downstream mental health will be key to reduce societal costs and improve quality of life for children, adolescents, and adults.

Spatio-Temporal Variation-Induced Group Disparity of Intra-Urban NO2 Exposure

Previous studies on exposure disparity have focused more on spatial variation but ignored the temporal variation of air pollution; thus, it is necessary to explore group disparity in terms of spatio-temporal variation to assist policy-making regarding public health. This study employed the dynamic land use regression (LUR) model and mobile phone signal data to illustrate the variation features of group disparity in Shanghai. The results showed that NO₂ exposure followed a bimodal, diurnal variation pattern and remained at a high level on weekdays but decreased on weekends. The most critical at-risk areas were within the central city in areas with a high population density. Moreover, women and the elderly proved to be more exposed to NO₂ pollution in Shanghai. Furthermore, the results of this study showed that it is vital to focus on land-use planning, transportation improvement programs, and population agglomeration to attenuate exposure inequality.

Nationwide and Regional PM2.5-Related Air Quality Health Benefits From the Removal of Energy-Related Emissions in the United States

Clean energy policy can provide substantial health benefits through improved air quality. As ambitious clean energy proposals are increasingly considered and adopted across the United States (US), quantifying the benefits of removal of such large air pollution emissions sources is crucial to understanding potential societal impacts of such policy. In this study, we estimate health benefits resulting from the elimination of emissions of fine particulate matter (PM_2.5), sulfur dioxide, and nitrogen oxides from the electric power, transportation, building, and industrial sectors in the contiguous US. We use EPA's CO-Benefits Risk Assessment screening tool to estimate health benefits resulting from the removal of PM_2.5-related emissions from these energy-related sectors. We find that nationwide efforts to eliminate energy-related emissions could prevent 53,200 (95% CI: 46,900-59,400) premature deaths each year and provide $608 billion ($537-$678 billion) in benefits from avoided PM_2.5-related illness and death. We also find that an average of 69% (range: 32%-95%) of the health benefits from emissions removal remain in the emitting region. Our study provides an indication of the potential scale and distribution of public health benefits that could result from ambitious regional and nationwide clean energy and climate mitigation policy.

Environmental inequality in the neighborhood networks of urban mobility in US cities

Exposure to air pollution within one’s residential neighborhood has detrimental consequences on health and well-being. Yet, this effect may be mitigated or exacerbated because individuals spend much of their time outside of their residential neighborhood to travel to neighborhoods across a city for work, errands, and leisure. Using mobile phone data to track neighborhood mobility in large US cities, I find that residents from minority and poor neighborhoods travel to neighborhoods that have greater air pollution levels than the neighborhoods that residents from White and nonpoor neighborhoods visit. These results reveal that minority and poor residents face environmental inequalities at three geographic scales: the neighborhoods they live in, their bordering neighborhoods, and the neighborhoods they visit.

Research has made clear that neighborhoods impact the health and well-being of their residents. A related strand of research shows that neighborhood disadvantage is geographically clustered. Because the neighborhoods of low-income and minority populations tend to be more disadvantaged, neighborhood conditions help explain racial and socioeconomic inequalities. These strands of research restrict processes of neighborhood influence to operate only within and between geographically contiguous neighbors. However, we are underestimating the role of neighborhood conditions in explaining inequality if disadvantage extends beyond the residential and extralocal environments into a network of neighborhoods spanning the urban landscape based on where residents move within a city. I use anonymized mobile phone data to measure exposure to air pollution among residents of poor and minority neighborhoods in 88 of the most populous US cities. I find that residents from minority and poor neighborhoods travel to neighborhoods that have greater air pollution levels than the neighborhoods that residents from White and nonpoor neighborhoods visit. Hispanic neighborhoods exhibit the greatest overall pollution burden, Black/White and Asian/White disparities are greatest at the network than residential scale, and the socioeconomic advantage of lower risk exposure is highest for residents from White neighborhoods. These inequalities are notable given recent declines in segregation and air pollution levels in American cities.

Exploring the distributional environmental justice implications of an air quality monitoring network in Los Angeles County

Non-governmental air quality monitoring networks include low-cost, networked air pollution sensors hosted at homes and schools that display real-time pollutant concentration estimates on publicly accessible websites. Such networks can empower people to take health-protective actions, but their unplanned organization may produce an uneven spatial distribution of sensors. Barriers to acquiring sensors may disenfranchise particular social groups. To test this directly, we quantitatively examine if there are social inequalities in the distribution of sensors in a non-governmental air quality monitoring network (PurpleAir) in Los Angeles County, California. We paired sociodemographic data from the American Community Survey and estimates of PM_2.5 concentrations from the USEPA's Downscaler model at the census tract level (n = 2203) with a sensors per capita (SPC) variable, which is based on population proximity to PurpleAir sensors (n = 696) in Los Angeles County. Findings from multivariable generalized estimating equations (GEEs) controlling for clustering by housing age and value reveal patterns of environmental injustice in the distribution of PurpleAir sensors across Los Angeles County census tracts. Tracts with higher percentages of Hispanic/Latino/a and Black residents and lower median household income had decreased SPC. There was a curvilinear (concave) relationship between the percentage of renter-occupants and SPC. Sensors were concentrated in tracts with greater percentages of adults and seniors (vs. children), higher occupied housing density, and higher PM_2.5 pollution. Results reveal social inequalities in the self-organizing PurpleAir network, suggesting another layer of environmental injustice such that residents of low-income and minority neighborhoods have reduced access to information about local air pollution.

Historical Redlining Is Associated with Present-Day Air Pollution Disparities in U.S. Cities

Communities of color in the United States are systematically exposed to higher levels of air pollution. We explore here how redlining, a discriminatory mortgage appraisal practice from the 1930s by the federal Home Owners' Loan Corporation (HOLC), relates to present-day intraurban air pollution disparities in 202 U.S. cities. In each city, we integrated three sources of data: (1) detailed HOLC security maps of investment risk grades [A ("best"), B, C, and D ("hazardous", i.e., redlined)], (2) year-2010 estimates of NO₂ and PM_2.5 air pollution levels, and (3) demographic information from the 2010 U.S. census. We find that pollution levels have a consistent and nearly monotonic association with HOLC grade, with especially pronounced (>50%) increments in NO₂ levels between the most (grade A) and least (grade D) preferentially graded neighborhoods. On a national basis, intraurban disparities for NO₂ and PM_2.5 are substantially larger by historical HOLC grade than they are by race and ethnicity. However, within each HOLC grade, racial and ethnic air pollution exposure disparities persist, indicating that redlining was only one of the many racially discriminatory policies that impacted communities. Our findings illustrate how redlining, a nearly 80-year-old racially discriminatory policy, continues to shape systemic environmental exposure disparities in the United States.

Historical Redlining Is Associated with Present-Day Air Pollution Disparities in U.S. Cities

Communities of color in the United States are systematically exposed to higher levels of air pollution. We explore here how redlining, a discriminatory mortgage appraisal practice from the 1930s by the federal Home Owners' Loan Corporation (HOLC), relates to present-day intraurban air pollution disparities in 202 U.S. cities. In each city, we integrated three sources of data: (1) detailed HOLC security maps of investment risk grades [A ("best"), B, C, and D ("hazardous", i.e., redlined)], (2) year-2010 estimates of NO₂ and PM_2.5 air pollution levels, and (3) demographic information from the 2010 U.S. census. We find that pollution levels have a consistent and nearly monotonic association with HOLC grade, with especially pronounced (>50%) increments in NO₂ levels between the most (grade A) and least (grade D) preferentially graded neighborhoods. On a national basis, intraurban disparities for NO₂ and PM_2.5 are substantially larger by historical HOLC grade than they are by race and ethnicity. However, within each HOLC grade, racial and ethnic air pollution exposure disparities persist, indicating that redlining was only one of the many racially discriminatory policies that impacted communities. Our findings illustrate how redlining, a nearly 80-year-old racially discriminatory policy, continues to shape systemic environmental exposure disparities in the United States.

Occupations and Sickness-Related Absences during the COVID-19 Pandemic

Pandemic frontline occupations consist of disproportionately low socioeconomic status and racial minority workers. Documenting occupational health disparities is therefore crucial for understanding COVID-19-related health inequalities in the United States. This study uses Current Population Survey microdata to estimate occupational differences in sickness-related absences (SAs) from work in March through June 2020 and their contribution to educational, racial-ethnic, and nativity health disparities. We find that there has been an unprecedented rise in SAs concentrated in transportation, food-related, and personal care and service occupations. SA rates were 6 times higher in these occupations than in non-health-care professions. The greatest increases were in occupations that are unsuitable for remote work, require workers to work close to others, pay low wages, and rarely provide health insurance. Workers in these occupations are disproportionately Black, Hispanic, indigenous, and immigrants. Occupation contributes 41% of the total of Black/white differences and 54% of educational differences in SAs.

Occupations and Sickness-Related Absences during the COVID-19 Pandemic

Pandemic frontline occupations consist of disproportionately low socioeconomic status and racial minority workers. Documenting occupational health disparities is therefore crucial for understanding COVID-19-related health inequalities in the United States. This study uses Current Population Survey microdata to estimate occupational differences in sickness-related absences (SAs) from work in March through June 2020 and their contribution to educational, racial-ethnic, and nativity health disparities. We find that there has been an unprecedented rise in SAs concentrated in transportation, food-related, and personal care and service occupations. SA rates were 6 times higher in these occupations than in non-health-care professions. The greatest increases were in occupations that are unsuitable for remote work, require workers to work close to others, pay low wages, and rarely provide health insurance. Workers in these occupations are disproportionately Black, Hispanic, indigenous, and immigrants. Occupation contributes 41% of the total of Black/white differences and 54% of educational differences in SAs.

Racial Disparities in the Heavy Metal Contamination of Urban Soil in the Southeastern United States

(1) Background: Field monitoring data for addressing the disproportional burden of exposure to soil contamination in communities of minority and low socioeconomic status (SES) are sparse. This study aims to examine the association between soil heavy metal levels, SES, and racial composition. (2) Methods: A total of 423 soil samples were collected in the urban areas of eight cities across six Southern states in the U.S., in 2015. Samples were analyzed using inductively coupled plasma–mass spectrometry (ICP–MS) for eight heavy metals. The association was examined with mixed models with the log-transformed metal concentrations as the dependent variables and rankings of low-income or minority percentages as the explanatory variables. (3) Results: Model results showed that soil metal concentrations were significantly associated with rankings of poverty and minority percentages. The cadmium concentration significantly increased by 4.7% (p-value < 0.01), for every 10 percentiles of increase in poverty rank. For every 10 percentiles of increase in minority rank, the soil concentrations were significantly up (p-values < 0.01) for arsenic (13.5%), cadmium (5.5%), and lead (10.6%). Minority rank had significant direct effects on both arsenic and lead. (4) Conclusions: The findings confirmed elevated heavy metal contamination in urban soil in low-income and/or predominantly minority communities.

The effects of air pollution, meteorological parameters, and climate change on COVID-19 comorbidity and health disparities: A systematic review

Air pollutants, especially particulate matter, and other meteorological factors serve as important carriers of infectious microbes and play a critical role in the spread of disease. However, there remains uncertainty about the relationship among particulate matter, other air pollutants, meteorological conditions and climate change and the spread of the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), hereafter referred to as COVID-19. A systematic review was conducted using PRISMA guidelines to identify the relationship between air quality, meteorological conditions and climate change, and COVID-19 risk and outcomes, host related factors, co-morbidities and disparities. Out of a total of 170,296 scientific publications screened, 63 studies were identified that focused on the relationship between air pollutants and COVID-19. Additionally, the contribution of host related-factors, co-morbidities, and health disparities was discussed. This review found a preponderance of evidence of a positive relationship between PM_2.5, other air pollutants, and meteorological conditions and climate change on COVID-19 risk and outcomes. The effects of PM_2.5, air pollutants, and meteorological conditions on COVID-19 mortalities were most commonly experienced by socially disadvantaged and vulnerable populations. Results however, were not entirely consistent, and varied by geographic region and study. Opportunities for using data to guide local response to COVID-19 are identified.

Disparities in Air Pollution Exposure in the United States by Race/Ethnicity and Income, 1990-2010

BACKGROUND

Few studies have investigated air pollution exposure disparities by race/ethnicity and income across criteria air pollutants, locations, or time.

OBJECTIVE

The objective of this study was to quantify exposure disparities by race/ethnicity and income throughout the contiguous United States for six criteria air pollutants, during the period 1990 to 2010.

METHODS

We quantified exposure disparities among racial/ethnic groups (non-Hispanic White, non-Hispanic Black, Hispanic (any race), non-Hispanic Asian) and by income for multiple spatial units (contiguous United States, states, urban vs. rural areas) and years (1990, 2000, 2010) for carbon monoxide (CO), nitrogen dioxide (NO 2 ), ozone (O 3 ), particulate matter with aerodynamic diameter ≤ 2.5 μ m (PM 2.5 ; excluding year-1990), particulate matter with aerodynamic diameter ≤ 10 μ m (PM 10 ), and sulfur dioxide (SO 2 ). We used census data for demographic information and a national empirical model for ambient air pollution levels.

RESULTS

For all years and pollutants, the racial/ethnic group with the highest national average exposure was a racial/ethnic minority group. In 2010, the disparity between the racial/ethnic group with the highest vs. lowest national-average exposure was largest for NO 2 [54% (4.6  ppb )], smallest for O 3 [3.6% (1.6  ppb )], and intermediate for the remaining pollutants (13%-19%). The disparities varied by U.S. state; for example, for PM 2.5 in 2010, exposures were at least 5% higher than average in 63% of states for non-Hispanic Black populations; in 33% and 26% of states for Hispanic and for non-Hispanic Asian populations, respectively; and in no states for non-Hispanic White populations. Absolute exposure disparities were larger among racial/ethnic groups than among income categories (range among pollutants: between 1.1 and 21 times larger). Over the period studied, national absolute racial/ethnic exposure disparities declined by between 35% (0.6 6 μ g / m 3 ; PM 2.5 ) and 88% (0.35  ppm ; CO); relative disparities declined to between 0.99 × (PM 2.5 ; i.e., nearly zero change) and 0.71 × (CO; i.e., a ∼ 29 % reduction).

DISCUSSION

As air pollution concentrations declined during the period 1990 to 2010, absolute (and to a lesser extent, relative) racial/ethnic exposure disparities also declined. However, in 2010, racial/ethnic exposure disparities remained across income levels, in urban and rural areas, and in all states, for multiple pollutants. https://doi.org/10.1289/EHP8584.

Resilience and Equity in a Time of Crises: Investing in Public Urban Greenspace Is Now More Essential Than Ever in the US and Beyond

The intersecting negative effects of structural racism, COVID-19, climate change, and chronic diseases disproportionately affect racial and ethnic minorities in the US and around the world. Urban populations of color are concentrated in historically redlined, segregated, disinvested, and marginalized neighborhoods with inadequate quality housing and limited access to resources, including quality greenspaces designed to support natural ecosystems and healthy outdoor activities while mitigating urban environmental challenges such as air pollution, heat island effects, combined sewer overflows and poor water quality. Disinvested urban environments thus contribute to health inequity via physical and social environmental exposures, resulting in disparities across numerous health outcomes, including COVID-19 and chronic diseases such as cancer and cardiovascular diseases (CVD). In this paper, we build off an existing conceptual framework and propose another conceptual framework for the role of greenspace in contributing to resilience and health equity in the US and beyond. We argue that strategic investments in public greenspaces in urban neighborhoods impacted by long term economic disinvestment are critically needed to adapt and build resilience in communities of color, with urgency due to immediate health threats of climate change, COVID-19, and endemic disparities in chronic diseases. We suggest that equity-focused investments in public urban greenspaces are needed to reduce social inequalities, expand economic opportunities with diversity in workforce initiatives, build resilient urban ecosystems, and improve health equity. We recommend key strategies and considerations to guide this investment, drawing upon a robust compilation of scientific literature along with decades of community-based work, using strategic partnerships from multiple efforts in Milwaukee Wisconsin as examples of success.

Ambient air pollution and ovarian cancer survival in California

OBJECTIVE

To examine whether exposure to ambient ozone, particulate matter with diameter less than 2.5 μm (PM_2.5), nitrogen dioxide (NO₂), and distance to major roadways (DTR) impact ovarian cancer-specific survival, while considering differences by stage, race/ethnicity, and socioeconomic status.

METHODS

Women diagnosed with epithelial ovarian cancer from 1996 to 2014 were identified through the California Cancer Registry and followed through 2016. Women's geocoded addresses were linked to pollutant exposure data and averaged over the follow-up period. Pollutants were considered independently and in multi-pollutant models. Cox proportional hazards models assessed hazards of disease-specific death due to environmental exposures, controlling for important covariates, with additional models stratified by stage at diagnosis, race/ethnicity and socioeconomic status.

RESULTS

PM_2.5 and NO₂, but not ozone or DTR, were significantly associated with survival in univariate models. In a multi-pollutant model for PM_2.5, ozone, and DTR, an interquartile range increase in PM_2.5 (Hazard Ratio [HR], 1.45; 95% Confidence Interval [CI], 1.41-1.49) was associated with worse prognosis. Similarly, in the multi-pollutant model with NO₂, ozone, and DTR, women with higher NO₂ exposures (HR for 20.0-30.0 ppb, 1.30; 95% CI, 1.25-1.36 and HR for >30.0 ppb, 2.48; 95% CI, 2.32-2.66) had greater mortality compared to the lowest exposed (<20.0 ppb). Stratified results show the effects of the pollutants differed by race/ethnicity and were magnified among women diagnosed in early stages.

CONCLUSIONS

Our analyses suggest that greater exposure to NO₂ and PM_2.5 may adversely impact ovarian cancer-specific survival, independent of sociodemographic and treatment factors. These findings warrant further study.

Social Susceptibility to Multiple Air Pollutants in Cardiovascular Disease

INTRODUCTION

Cardiovascular disease (CVD) is the leading cause of death in the United States, and substantial research has linked ambient air pollution to elevated rates of CVD etiology and events. Much of this research identified increased effects of air pollution in lower socioeconomic position (SEP) communities, where pollution exposures are also often higher. The complex spatial confounding between air pollution and SEP makes it very challenging, however, to disentangle the impacts of these very different exposure types and to accurately assess their interactions. The specific causal components (i.e., specific social stressors) underlying this SEP-related susceptibility remain unknown, because there are myriad pathways through which poverty and/or lower-SEP conditions may influence pollution susceptibility - including diet, smoking, coexposures in the home and occupational environments, health behaviors, and healthcare access. Growing evidence suggests that a substantial portion of SEP-related susceptibility may be due to chronic psychosocial stress - given the known wide-ranging impacts of chronic stress on immune, endocrine, and metabolic function - and to a higher prevalence of unpredictable chronic stressors in many lower-SEP communities, including violence, job insecurity, and housing instability. As such, elucidating susceptibility to pollution in the etiology of CVD, and in the risk of CVD events, has been identified as a research priority. This interplay among social and environmental conditions may be particularly relevant for CVD, because pollution and chronic stress both impact inflammation, metabolic function, oxidative stress, hypertension, atherosclerosis, and other processes relevant to CVD etiology. Because pollution exposures are often spatially patterned by SEP, disentangling their effects - and quantifying any interplay - is especially challenging. Doing so, however, would help to improve our ability to identify and characterize susceptible populations and to improve our understanding of how community stressors may alter responses to multiple air pollutants. More clearly characterizing susceptible populations will improve our ability to design and target interventions more effectively (and cost-effectively) and may reveal greater benefits of pollution reduction in susceptible communities, strengthening cost-benefit and accountability analyses, ultimately reducing the disproportionate burden of CVD and reducing health disparities.

METHODS

In the current study, we aimed to quantify combined effects of multiple pollutants and stressor exposures on CVD events, using a number of unique datasets we have compiled and verified, including the following. 1. Poverty metrics, violent crime rates, a composite socioeconomic deprivation index (SDI), an index of racial and economic segregation, noise disturbance metrics, and three composite spatial factors produced from a factor analysis of 27 community stressors. All indicators have citywide coverage and were verified against individual reports of stress and stressor exposure, in citywide focus groups and surveys. 2. Spatial surfaces for multiple pollutants from the New York City (NYC) Community Air Survey (NYCCAS), which monitored multiple pollutants year-round at 150 sites and used land use regression (LUR) modeling to estimate fine-scale (100-m) intra-urban spatial variance in fine particles (PM2.5), nitrogen dioxide (NO2), sulfur dioxide (SO2), and ozone (O3). 3. Daily data and time-trends derived from all U.S. Environmental Protection Agency (EPA) Air Quality System (AQS) monitors in NYC for 2005-2011, which we combined with NYCCAS surfaces to create residence- and day-specific spatiotemporal exposure estimates. 4. Complete data on in- and out-patient unscheduled CVD events presented in NYC hospitals for 2005-2011 (n = 1,113,185) from the New York State (NYS) Department of Health's Statewide Planning and Research Cooperative System (SPARCS). In the study, we quantified relationships between multiple pollutant exposures and both community CVD event rates and individual risk of CVD events in NYC and tested whether pollution-CVD associations varied by community SEP and social stressor exposures. We hypothesized (1) that greater chronic community-level SEP, stressor, and pollution exposures would be associated with higher community CVD rates; (2) that spatiotemporal variations in multiple pollutants would be associated with excess risk of CVD events; and (3) that pollution-CVD associations would be stronger in communities of lower SEP or higher stressor exposures.

RESULTS

To first understand the separate and combined associations with CVD for both stressors and pollutants measured at the same spatial and temporal scale of resolution, we used ecological cross-sectional models to examine spatial relationships between multiple chronic pollutant and stressor exposures and age-adjusted community CVD rates. Using census-tract-level annual averages (n = 2,167), we compared associations with CVD rates for multiple pollutant concentrations and social stressors. We found that associations with community CVD rates were consistently stronger for social stressors than for pollutants, in terms of both magnitude and significance. We note, however, that this result may be driven by the relatively greater variation (on a proportional basis) for stressors than for pollutants in NYC. We also tested effect modification of pollutant-CVD associations by each social stressor and found evidence of stronger associations for NO2, PM2.5, and wintertime SO2 with CVD rates, particularly across quintiles of increasing community violence or assault rates (P trend < 0.0001). To examine individual-level associations between spatiotemporal exposures to multiple pollutants and the risk of CVD events, across multiple lag days, we examined the combined effects of multiple pollutant exposures, using spatiotemporal (day- and residence-specific) pollution exposure estimates and hospital data on individual CVD events in case-crossover models, which inherently adjust for nontime-varying individual confounders (e.g., sex and race) and comorbidities. We found consistent significant relationships only for same-day pollutant exposures and the risk of CVD events, suggesting very acute impacts of pollution on CVD risk. Associations with CVD were positive for NO2, PM2.5, and SO2, as hypothesized, and we found inverse associations for O3 (a secondary pollutant chemically decreased ["scavenged"] by fresh emissions that, in NYC, displays spatial and temporal patterns opposite those of NO2). Finally, to test effect modification by chronic community social stressors on the relationships between spatiotemporal pollution measures and the risk of CVD events, we used individual-level case-crossover models, adding interaction terms with categorical versions of each social stressor. We found that associations between NO2 and the risk of CVD events were significantly elevated only in communities with the highest exposures to social stressors (i.e., in the highest quintiles of poverty, socioeconomic deprivation, violence, or assault). The largest positive associations for PM2.5 and winter SO2 were generally found in the highest-stressor communities but were not significant in any quintile. We again found inverse associations for O3, which were likewise stronger for individuals living in communities with greater stressor exposures.

CONCLUSIONS

In ecological models, we found stronger relationships with community CVD rates for social stressors than for pollutant exposures. In case-crossover analyses, higher exposures to NO2, PM2.5, and SO2 were associated with greater excess risk of CVD events but only on the case day (there were no consistent significant lagged-day effects). In effect-modification analyses at both the community and individual level, we found evidence of stronger pollution-CVD associations in communities with higher stressor exposures. Given substantial spatial confounding across multiple social stressors, further research is needed to disentangle these effects in order to identify the predominant social stressors driving this observed differential susceptibility.

Multigenerational immigrant trajectories and children's unequal exposure to fine particulate matter in the US

Fine particulate matter is a serious health threat and exposures are particularly damaging for children. The environmental justice (EJ) literature shows that racial/ethnic minority communities experience disproportionate exposure to particulate pollution in the US. While important, those EJ studies tend to neglect people's complex identities, including their nativity and their families' generational histories of residence in the US. Yet there is growing interest in the intersection of immigrant populations and EJ. Our use of individual-level data enables examination of immigrant generational status by race/ethnicity, which provides insights on the intergenerational persistence of environmental injustice. We pair data on 12,570 US third graders (from 2013 to 2014) collected through the Early Childhood Longitudinal Survey with PM_2.5 concentrations for the census tracts of their home and school locations. We apply generalized estimating equations to test for intergenerational disparities in exposure and to examine how those disparities vary between racial/ethnic groups. Independent of race/ethnicity, first- and second-generation children have greater PM_2.5 exposure than 2.5- and third-generation children. However, generational status disparities in exposures vary based on race/ethnicity. First-generation White children face greater exposure than White children of later generational statuses, with inequalities attenuating by the second generation. In contrast, Hispanic/Latinx children experience no significant drop in exposure until the third generation. Among Asian and Black children, generational status was not a significant determinant of exposure. Results quantify the intergenerational persistence of environmental injustices for persons of color while showing the amelioration of inequalities for Whites after just one generation is born in the US, reflecting another facet of White privilege in the US.

Traffic-Related Air Pollution and Incident Dementia: Direct and Indirect Pathways Through Metabolic Dysfunction

BACKGROUND

Ambient air pollution exposure has been associated with dementia. Additionally, epidemiologic evidence supports associations between air pollution and diabetes as well as diabetes and dementia. Thus, an indirect pathway between air pollution and dementia may exist through metabolic dysfunction.

OBJECTIVE

To investigate whether local traffic-related air pollution (TRAP) influences incident dementia and cognitive impairment, non-dementia (CIND) in a cohort of older Mexican Americans. We also assess how much of this estimated effect might be mediated through type 2 diabetes (T2DM).

METHODS

In a 10-year, prospective study of Latinos (n = 1,564), we generated TRAP-NOx as a surrogate for pollution from local traffic sources at participants' residences during the year prior to enrollment. We used Cox proportional hazards modeling and mediation analysis to estimate the effects of TRAP-NOx on dementia and/or CIND and indirect pathways operating through T2DM.

RESULTS

Higher TRAP-NOx was associated with incident dementia (HR = 1.55 for the highest versus lower tertiles, 95% CI = 1.04, 2.55). Higher TRAP-NOx was also associated with T2DM (OR = 1.62, 95% CI = 1.27, 2.05); furthermore, T2DM was associated with dementia (HR = 1.94, 95% CI = 1.42, 2.66). Mediation analysis indicated that 20% of the estimated effect of TRAP-NOx on dementia/CIND was mediated through T2DM.

CONCLUSION

Our results suggest that exposure to local traffic-related air pollution is associated with incident dementia. We also estimated that 20% of this effect is mediated through T2DM. Thus, ambient air pollution might affect brain health via direct damage as well as through indirect pathways related to diabetes and metabolic dysfunction.

Confounding by Socioeconomic Status in Epidemiological Studies of Air Pollution and Health: Challenges and Opportunities

BACKGROUND

Despite a vast air pollution epidemiology literature to date and the recognition that lower-socioeconomic status (SES) populations are often disproportionately exposed to pollution, there is little research identifying optimal means of adjusting for confounding by SES in air pollution epidemiology, nor is there a strong understanding of biases that may result from improper adjustment.

OBJECTIVE

We aim to provide a conceptualization of SES and a review of approaches to its measurement in the U.S. context and discuss pathways by which SES may influence health and confound effects of air pollution. We explore bias related to measurement and operationalization and identify statistical approaches to reduce bias and confounding.

DISCUSSION

Drawing on the social epidemiology, health geography, and economic literatures, we describe how SES, a multifaceted construct operating through myriad pathways, may be conceptualized and operationalized in air pollution epidemiology studies. SES varies across individuals within the contexts of place, time, and culture. Although no single variable or index can fully capture SES, many studies rely on only a single measure. We recommend examining multiple facets of SES appropriate to the study design. Furthermore, investigators should carefully consider the multiple mechanisms by which SES might be operating to identify those SES indicators that may be most appropriate for a given context or study design and assess the impact of improper adjustment on air pollution effect estimates. Last, exploring model contraction and expansion methods may enrich adjustment, whereas statistical approaches, such as quantitative bias analysis, may be used to evaluate residual confounding. https://doi.org/10.1289/EHP7980.

Racial Difference in the Association of Long-Term Exposure to Fine Particulate Matter (PM2.5) and Cardiovascular Disease Mortality among Renal Transplant Recipients

Ambient air pollutants are known risk factors for cardiovascular disease (CVD) morbidity and mortality with significant racial disparities. However, few studies have explored racial differences among highly susceptible subpopulations, such as renal transplant recipients (RTRs). Despite improvements in quality of life after transplantation, CVD remains the major cause of mortality, especially among Black recipients. This study aimed to evaluate potential racial differences in the association between long-term levels of PM2.5 and the risk of all-cause, total CVD, and coronary heart disease (CHD) mortality among RTRs. This retrospective study consists of 93,857 non-smoking adults who received a renal transplant between 2001 and 2015. Time-dependent Cox regression was used to assess the association between annual concentrations of PM2.5 and mortality risk. In the multivariable-adjusted models, a 10 μg/m3 increase in ambient PM2.5 levels found increased risk of all-cause (HR = 3.45, 95% CI: 3.08-3.78), CVD (HR = 2.38, 95% CI: 1.94-2.92), and CHD mortality (HR = 3.10, 95% CI: 1.96-4.90). Black recipients had higher risks of all-cause (HR = 4.09, 95% CI: 3.43-4.88) and CHD mortality (HR = 6.73, 95% CI: 2.96-15.32). High levels of ambient PM2.5 were associated with all-cause, CVD, and CHD mortality. The association tended to be higher among Black recipients than non-Blacks.

Inferential challenges when assessing racial/ethnic health disparities in environmental research

Numerous epidemiologic studies have documented environmental health disparities according to race/ethnicity (R/E) to inform targeted interventions aimed at reducing these disparities. Yet, the use of R/E under the potential outcomes framework implies numerous underlying assumptions for epidemiologic studies that are often not carefully considered in environmental health research. In this commentary, we describe the current state of thinking about the interpretation of R/E variables in etiologic studies. We then discuss how such variables are commonly used in environmental epidemiology. We observed three main uses for R/E: i) as a confounder, ii) as an effect measure modifier and iii) as the main exposure of interest either through descriptive analysis or under a causal framework. We identified some common methodological concerns in each case and provided some practical solutions. The use of R/E in observational studies requires particular cautions in terms of formal interpretation and this commentary aims at providing a practical resource for future studies assessing racial/ethnic health disparities in environmental research.

The Longitudinal Revolution: Sociological research at the 50-year milestone of the Panel Study of Income Dynamics

The U.S. Panel Study of Income Dynamics (PSID) celebrated its 50th anniversary in 2018. Initially designed to assess the nation's progress in combatting poverty, PSID's scope broadened quickly to a variety of topics and fields of inquiry. To date, sociologists are the second-most frequent users of PSID data after economists. Here, we describe the ways in which PSID's history reflects shifts in social science scholarship and funding priorities over half a century, take stock of the most important sociological breakthroughs it facilitated, in particular those relying on the longitudinal structure of the data, and critically assess the unique advantages and limitations of the PSID and surveys like it for today's sociological scholarship.

Enhancing life cycle chemical exposure assessment through ontology modeling

In its 2014 report, A Framework Guide for the Selection of Chemical Alternatives, the National Academy of Sciences placed increased emphasis on comparative exposure assessment throughout the life cycle (i.e., from manufacturing to end-of-life) of a chemical. The inclusion of the full life cycle greatly increases the data demands for exposure assessments, including both the quantity and type of data. High throughput tools for exposure estimation add to this challenge by requiring rapid accessibility to data. In this work, ontology modeling was used to bridge the domains of exposure modeling and life cycle inventory modeling to facilitate data sharing and integration. The exposure ontology, ExO, is extended to describe human exposure to consumer products, while an inventory modeling ontology, LciO, is formulated to support automated data mining. The core ontology pieces are connected using a bridging ontology and discussed through a theoretical example to demonstrate how data from LCA can be leveraged to support rapid exposure modeling within a life cycle context.

Is geography destiny? Disrupting the relationship between segregation and neighbohrood outcomes

Considerable research has shown that, in the cross-section, segregation is associated with detrimental neighborhood outcomes for blacks and improved neighborhood outcomes for whites. However, it is unclear whether early-life experiences of segregation shape later-life neighborhood outcomes, whether this association persists for those who migrate out of the metropolitan areas in which they grew up, and how these relationships differ for blacks and whites. Using the Panel Study of Income Dynamics from 1979 to 2013, we find that the level of segregation experienced during adolescence is associated with significantly worse neighborhood outcomes in adulthood for blacks. However, migrating out of the metropolitan area an individual grew up in substantially moderates these relationships. In contrast, adolescent segregation is associated with improved, or not significantly different, neighborhood outcomes in adulthood for whites. These findings have important implications for theorizing about the mechanisms linking segregation and neighborhood outcomes and for considering potential means of assuaging racial disparities in harmful neighborhood exposures.

Racialized Structural Vulnerability: Neighborhood Racial Composition, Concentrated Disadvantage, and Fine Particulate Matter in California

This study contributes to previous research by advancing a “racialized structural vulnerability” framework and presenting a new empirical analysis of the relationship between neighborhood Asian, Black, and Latinx composition; extrinsic and intrinsic vulnerability; and PM_2.5 exposures in California with secondary data from 2004–2014. Principal component analyses revealed that tract Latinx composition was highly correlated with extrinsic vulnerability (economic disadvantage and limited English-speaking ability), and that tract Black composition was highly correlated with intrinsic vulnerability (elevated prevalence of asthma-related emergency department visits and low birth weight). Spatial lag regression models tested hypotheses regarding the association between Asian, Black, and Latinx population vulnerability factors and the 2009–2011 annual average PM_2.5 percentile rankings, net of emissions and spatial covariates. Results indicated that the percent Latinx population, followed by the regional clustering of PM_2.5, and the percent of non-Latinx Black and non-Latinx Asian population were the strongest positive multivariable correlates of PM_2.5 percentile rankings, net of other factors. Additional analyses suggested that despite shifting demographic and spatial correlates of 2012–2014 PM_2.5 exposures, the tracts’ Black and Latinx composition and location in the San Joaquin Valley remain important vulnerability factors with implications for future research and policy.

Advancing the symptom science model with environmental health

OBJECTIVE

Globally, indoor and outdoor pollutants are leading risk factors for death and reduced quality of life. Few theories explicitly address environmental health within the nursing discipline with a focus on harmful environmental exposures. The objective here is to expand the National Institutes of Health Symptom Science Model to include the environmental health concepts of environmental endotype (causative pathway) and environmental exposure.

DESIGN

Meleis' research to theory strategy for theory refinement was used. Research workshop proceedings, environmental health nursing research expert consensus, panelist research trajectories, and review of the literature were utilized as data sources.

RESULTS

Ongoing emphasis on the physical environment as a key determinant of health and theoretical perspectives for including environmental exposures and endotypes in symptom science are presented. Definitions of these concepts, further developed, are provided. Recommendations to strengthen environmental health nursing research and practice through capacity building/infrastructure, methods/outcomes, translational/clinical research, and basic/mechanistic research are included.

CONCLUSION

The revised model deepens theoretical support for clinical actions that include environmental modification, environmental health education, and exposure reduction. This modification will enable a middle-range theory and shared mental model to inspire the prioritization of environmental health in nursing leadership, research, practice, and education.

The impact of air exchange rate on ambient air pollution exposure and inequalities across all residential parcels in Massachusetts

Individual housing characteristics can modify outdoor ambient air pollution infiltration through air exchange rate (AER). Time and labor-intensive methods needed to measure AER has hindered characterization of AER distributions across large geographic areas. Using publicly-available data and regression models associating AER with housing characteristics, we estimated AER for all Massachusetts residential parcels. We conducted an exposure disparities analysis, considering ambient PM_2.5 concentrations and residential AERs. Median AERs (h^-1) with closed windows for winter and summer were 0.74 (IQR: 0.47-1.09) and 0.36 (IQR: 0.23-0.57), respectively, with lower AERs for single family homes. Across residential parcels, variability of indoor PM_2.5 concentrations of ambient origin was twice that of ambient PM_2.5 concentrations. Housing parcels above the 90th percentile of both AER and ambient PM_2.5 (i.e., the leakiest homes in areas of highest ambient PM_2.5)-vs. below the 10 percentile-were located in neighborhoods with higher proportions of Hispanics (20.0% vs. 2.0%), households with an annual income of less than $20,000 (26.0% vs. 7.5%), and individuals with less than a high school degree (23.2% vs. 5.8%). Our approach can be applied in epidemiological studies to estimate exposure modifiers or to characterize exposure disparities that are not solely based on ambient concentrations.

Residential Segregation and Racial/Ethnic Disparities in Ambient Air Pollution

Race and ethnicity are consequential constructs when it comes to exposure to air pollution. Persistent environmental racial/ethnic inequalities call for attention to identifying the factors that maintain them. We examined associations between racial residential segregation and racial/ethnic inequalities in exposure to three types of air pollutants. Using data from the Panel Study of Income Dynamics (1990-2011), the U.S. Census (1990- 2010), and the Environmental Protection Agency, we tested the independent and joint contributions of race/ethnicity and metropolitan-level residential segregation on individual levels of exposure to air pollution nationwide. We found that racial and ethnic minorities were exposed to significantly higher levels of air pollution compared to Whites. The difference between minorities and Whites in exposure to all three types of air pollution was most pronounced in metropolitan areas with high levels of residential segregation. The environmental inequities observed in this study call for public health and policy initiatives to ameliorate the sources of racial/ethnic gaps in pollution exposure. Given the links between the physical environment and health, addressing such uneven environmental burdens may be a promising way to improve population health and decrease racial/ethnic inequalities therein.

Migration, Mobility, and Neighborhood Attainment: Using the PSID to Understand the Processes of Racial Stratification

In this article we describe the considerable influence of the Panel Study of Income Dynamics (PSID) on research on residential migration, mobility, and neighborhood attainment, as well as the role of PSID-based research in housing policy debates. We review some of the central research findings and key discoveries that have come from analyses that have used the PSID. We then present new research, using PSID data that are linked to geographic data, to demonstrate how geographic moves are associated with changes in neighborhood poverty rates. The relationship differs markedly for blacks and whites, and our results add to a body of work that shows sharp racial differences in residential context, and the role that personal migration plays in shaping this stratification. Finally, we use these findings and the shortcomings of past research to prescribe ways that the PSID could be enhanced to understand more about migration dynamics and processes of residential stratification.

Early-Life Air Pollution Exposure, Neighborhood Poverty, and Childhood Asthma in the United States, 1990⁻2014

Ambient air pollution is a well-known risk factor of various asthma-related outcomes, however, past research has often focused on acute exacerbations rather than asthma development. This study draws on a population-based, multigenerational panel dataset from the United States to assess the association of childhood asthma risk with census block-level, annual-average air pollution exposure measured during the prenatal and early postnatal periods, as well as effect modification by neighborhood poverty. Findings suggest that early-life exposures to nitrogen dioxide (NO₂), a marker of traffic-related pollution, and fine particulate matter (PM2.5), a mixture of industrial and other pollutants, are positively associated with subsequent childhood asthma diagnosis (OR = 1.25, 95% CI = 1.10⁻1.41 and OR = 1.25, 95% CI = 1.06⁻1.46, respectively, per interquartile range (IQR) increase in each pollutant (NO₂ IQR = 8.51 ppb and PM2.5 IQR = 4.43 µ/m³)). These effects are modified by early-life neighborhood poverty exposure, with no or weaker effects in moderate- and low- (versus high-) poverty areas. This work underscores the importance of a holistic, developmental approach to elucidating the interplay of social and environmental contexts that may create conditions for racial-ethnic and socioeconomic disparities in childhood asthma risk.

Ambient Air Pollution and Asthma-Related Outcomes in Children of Color of the USA: a Scoping Review of Literature Published Between 2013 and 2017

PURPOSE OF REVIEW

Given racial disparities in ambient air pollution (AAP) exposure and asthma risk, this review offers an overview of the literature investigating the ambient air pollution-asthma relationship in children of color between 2013 and 2017.

RECENT FINDINGS

AAP is likely a key contributor to the excess burden of asthma in children of color due to pervasive exposure before birth, at home, and in school. Recent findings suggest that psychosocial stressors may modify the relationship between AAP and asthma. The effect of AAP on asthma in children of color is likely modulated by multiple unique psychosocial stressors and gene-environment interactions. Although children of color are being included in asthma studies, more research is still needed on impacts of specific criteria pollutants throughout the life course. Additionally, future studies should consider historical factors when analyzing current exposure profiles.

Temporal trends in air pollution exposure inequality in Massachusetts

Mounting evidence over the past several decades has demonstrated inequitable distribution of pollutants of ambient origin between sociodemographic groups in the United States. Most environmental inequality studies to date are cross-sectional and used proximity-based methods rather than modeled air pollution concentrations, limiting the ability to examine trends over time or the factors that drive exposure inequalities. In this paper, we use 1km² modeled PM_2.5 and NO₂ concentrations in Massachusetts over an 8-year period and Census demographic data to quantify inequality between sociodemographic groups and to develop a more nuanced understanding of the drivers and trends in longitudinal air pollution inequality. Annual-average population-weighted PM_2.5 and NO₂ concentrations were highest for urban non-Hispanic black populations (11.8µg/m³ in 2003 and 8.4µg/m³ in 2010, vs. 11.3µg/m³ and 8.1µg/m³ for urban non-Hispanic whites) and urban Hispanic populations (15.9 ppb in 2005 and 13.0 ppb in 2010, vs. 13.0 ppb and 10.2 ppb for urban non-Hispanic whites), respectively. While population groups experienced similar absolute decreases in exposure over time, disparities in population-weighted concentrations increased over time when quantified by the Atkinson Index, a relative inequality measure. Exposure inequalities were approximately one order of magnitude greater for NO₂ compared to PM_2.5, were more pronounced in urban compared to rural geographies, and between racial/ethnic groups compared to income and educational attainment groups. Our results also revealed similar longitudinal PM_2.5 and NO₂ inequality trends using Census 2000 and Census 2010 data, indicating that spatio-temporal shifts in air pollution may best explain observed trends in inequality. These findings enhance our understanding of factors that contribute to persistent inequalities and underscore the importance of targeted exposure reduction strategies aimed at vulnerable populations and neighborhoods.