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

Paving a Path to Equity in Cardiorenal Care

Cardiorenal syndrome encompasses a dynamic interplay between cardiovascular and kidney disease, and its prevention requires careful examination of multiple predisposing underlying conditions. The unequal distribution of diabetes, heart failure, hypertension, and kidney disease requires special attention because of the influence of these conditions on cardiorenal disease. Despite growing evidence regarding the benefits of disease-modifying agents (e.g., sodium-glucose cotransporter 2 inhibitors) for cardiovascular, kidney, and metabolic (CKM) disease, significant disparities remain in access to and utilization of these essential therapeutics. Multilevel barriers impeding their use require multisector interventions that address patient, provider, and health system-tailored strategies. Burgeoning literature also describes the critical role of unequal social determinants of health, or the sociopolitical contexts in which people live and work, in cardiorenal risk factors, including heart failure, diabetes, and chronic kidney disease. This review outlines (i) inequality in the burden and treatment of hypertension, type 2 diabetes, and heart failure; (ii) disparities in the use of key disease-modifying therapies for CKM diseases; and (iii) multilevel barriers and solutions to achieve greater pharmacoequity in the use of disease-modifying therapies. In addition, this review provides summative evidence regarding the role of unequal social determinants of health in cardiorenal health disparities, further outlining potential considerations for future research and intervention. As proposed in the 2023 American Heart Association presidential advisory on CKM health, a paradigm shift will be needed to achieve cardiorenal health equity. Through a deeper understanding of CKM health and a commitment to equity in the prevention, detection, and treatment of CKM disease, we can achieve this critical goal. Semin Nephrol 36:x-xx © 20XX Elsevier Inc. All rights reserved.

Health impact assessment of PM2.5 from uncovered coal trains in the San Francisco Bay Area: Implications for global exposures

Coal generates almost 40% of the world's electricity with 80 countries throughout the world using coal power. An inherent part of this generation is the rail transport of coal in uncovered cars, often up to a mile long. Existing studies document the subsequent increments of PM2.5 to the near-rail populations, which typically include a large number of economically disadvantaged residents and/or people of color. However, to date there is no assessment of the health implications of this stage in the use of coal. The present study quantifies such impacts on a region in the San Francisco Bay Area. The analysis shows important effects on mortality, hospitalization for cardiovascular and respiratory disease, asthma exacerbation, work loss, and days of restricted activity. Several of these outcomes exhibited a one to six percent increase over baseline. As such, it delineates the implications for the global effects of the transport of coal.

Historical redlining is associated with disparities in wildlife biodiversity in four California cities

Legacy effects describe the persistent, long-term impacts on an ecosystem following the removal of an abiotic or biotic feature. Redlining, a policy that codified racial segregation and disinvestment in minoritized neighborhoods, has produced legacy effects with profound impacts on urban ecosystem structure and health. These legacies have detrimentally impacted public health outcomes, socioeconomic stability, and environmental health. However, the collateral impacts of redlining on wildlife communities are uncertain. Here, we investigated whether faunal biodiversity was associated with redlining. We used home-owner loan corporation (HOLC) maps [grades A (i.e., "best" and "greenlined"), B, C, and D (i.e., "hazardous" and "redlined")] across four cities in California and contributory science data (iNaturalist) to estimate alpha and beta diversity across six clades (mammals, birds, insects, arachnids, reptiles, and amphibians) as a function of HOLC grade. We found that in greenlined neighborhoods, unique species were detected with less sampling effort, with redlined neighborhoods needing over 8,000 observations to detect the same number of unique species. Historically redlined neighborhoods had lower native and nonnative species richness compared to greenlined neighborhoods across each city, with disparities remaining at the clade level. Further, community composition (i.e., beta diversity) consistently differed among HOLC grades for all cities, including large differences in species assemblage observed between green and redlined neighborhoods. Our work spotlights the lasting effects of social injustices on the community ecology of cities, emphasizing that urban conservation and management efforts must incorporate an antiracist, justice-informed lens to improve biodiversity in urban environments.

Socioeconomic and sociodemographic correlations to COVID-19 variability in the United States in 2020

The COVID-19 pandemic provided an additional spotlight on the longstanding socioeconomic/health impacts of redlining and has added to the myriad of environmental justice issues, which has caused significant loss of life, health, and productive work. The Centers for Disease Control and Prevention (CDC) reports that a person with any selected underlying health conditions is more likely to experience severe COVID-19 symptoms, with more than 81% of COVID-19-related deaths among people aged 65 years and older. The effects of COVID-19 are not homogeneous across populations, varying by socioeconomic status, PM2.5 exposure, and geographic location. This variability is supported by analysis of existing data as a function of the number of cases and deaths per capita/1,00,000 persons. We investigate the degree of correlation between these parameters, excluding health conditions and age. We found that socioeconomic variables alone contribute to ~40% of COVID-19 variability, while socioeconomic parameters, combined with political affiliation, geographic location, and PM2.5 exposure levels, can explain ~60% of COVID-19 variability per capita when using an OLS regression model; socioeconomic factors contribute ~28% to COVID-19-related deaths. Using spatial coordinates in a Random Forest (RF) regressor model significantly improves prediction accuracy by ~120%. Data visualization products reinforce the fact that the number of COVID-19 deaths represents 1% of COVID-19 cases in the US and globally. A larger number of democratic voters, larger per-capita income, and age >65 years is negatively correlated (associated with a decrease) with the number of COVID cases per capita. Several distinct regions of negative and positive correlations are apparent, which are dominated by two major regions of anticorrelation: (1) the West Coast, which exhibits high PM2.5 concentrations and fewer COVID-19 cases; and (2) the middle portion of the US, showing mostly high number of COVID-19 cases and low PM2.5 concentrations. This paper underscores the importance of exercising caution and prudence when making definitive causal statements about the contribution of air quality constituents (such as PM2.5) and socioeconomic factors to COVID-19 mortality rates. It also highlights the importance of implementing better health/lifestyle practices and examines the impact of COVID-19 on vulnerable populations, particularly regarding preexisting health conditions and age. Although PM2.5 contributes comparable deaths (~7M) per year, globally as smoking cigarettes (~8.5M), quantifying any causal contribution toward COVID-19 is non-trivial, given the primary causes of COVID-19 death and confounding factors. This becomes more complicated as air pollution was reduced significantly during the lockdowns, especially during 2020. This statistical analysis provides a modular framework, that can be further expanded with the context of multilevel analysis (MLA). This study highlights the need to address socioeconomic and environmental disparities to better prepare for future pandemics. By understanding how factors such as socioeconomic status, political affiliation, geographic location, and PM2.5 exposure contribute to the variability in COVID-19 outcomes, policymakers and public health officials can develop targeted strategies to protect vulnerable populations. Implementing improved health and lifestyle practices and mitigating environmental hazards will be essential in reducing the impact of future public health crises on marginalized communities. These insights can guide the development of more resilient and equitable health systems capable of responding effectively to similar future scenarios.

NPCC4: New York City climate risk information 2022-observations and projections

New York City (NYC) faces many challenges in the coming decades due to climate change and its interactions with social vulnerabilities and uneven urban development patterns and processes. This New York City Panel on Climate Change (NPCC) report contributes to the Panel's mandate to advise the city on climate change and provide timely climate risk information that can inform flexible and equitable adaptation pathways that enhance resilience to climate change. This report presents up-to-date scientific information as well as updated sea level rise projections of record. We also present a new methodology related to climate extremes and describe new methods for developing the next generation of climate projections for the New York metropolitan region. Future work by the Panel should compare the temperature and precipitation projections presented in this report with a subset of models to determine the potential impact and relevance of the "hot model" problem. NPCC4 expects to establish new projections-of-record for precipitation and temperature in 2024 based on this comparison and additional analysis. Nevertheless, the temperature and precipitation projections presented in this report may be useful for NYC stakeholders in the interim as they rely on the newest generation of global climate models.

Black-White Disparities in Asthma Hospitalizations and ED Visits Among Medicaid-Enrolled Children

BACKGROUND AND OBJECTIVES

Asthma is a common, potentially serious childhood chronic condition that disproportionately afflicts Black children. Hospitalizations and emergency department (ED) visits for asthma can often be prevented. Nearly half of children with asthma are covered by Medicaid, which should facilitate access to care to manage and treat symptoms. We provide new evidence on racial disparities in asthma hospitalizations and ED visits among Medicaid-enrolled children.

METHODS

We used comprehensive Medicaid claims data from the Transformed Medicaid Statistical Information System. Our study population included 279 985 Medicaid-enrolled children with diagnosed asthma. We identified asthma hospitalizations and ED visits occurring in 2019. We estimated differences in the odds of asthma hospitalizations and ED visits for non-Hispanic Black versus non-Hispanic white children, adjusting for sex, age, Medicaid eligibility group, Medicaid plan type, state, and rurality.

RESULTS

In 2019, among Black children with asthma, 1.2% had an asthma hospitalization and 8.0% had an asthma ED visit compared with 0.5% and 3.4% of white children with a hospitalization and ED visit, respectively. After adjusting for other characteristics, the rates for Black children were more than twice the rates for white children (hospitalization adjusted odds ratio 2.45, 95% confidence interval 2.23-2.69; ED adjusted odds ratio 2.42; 95% confidence interval 2.33-2.51).

CONCLUSIONS

There are stark racial disparities in asthma hospitalizations and ED visits among Medicaid-enrolled children with asthma. To diminish these disparities, it will be important to implement solutions that address poor quality care, discriminatory treatment in health care settings, and the structural factors that disproportionately expose Black children to asthma triggers and access barriers.

Reproductive and Social Policies, Sociopolitical Stress, and Implications for Maternal and Child Health Equity

PURPOSE OF REVIEW

Although many environmental exposures (e.g., air pollution) are geographically patterned and persist as a result of historic economic policies (e.g., redlining), the impact of reproductive and social policies on maternal and child health remains incompletely understood. Reproductive and social policies are increasingly important for maternal and child health equity, particularly following the 2022 US Supreme Court decision in Dobbs v Jackson Women's Health Organization ("Dobbs decision"), which restricted access to abortion. Here, we summarize the literature from original research studies examining influences of reproductive and social policy on maternal and child health, focusing on impacts on adverse birth outcomes and policies as sources of stress.

RECENT FINDINGS

Several studies suggest that those most impacted by the Dobbs decision are younger, non-white, socioeconomically disadvantaged, and living in states with less access to government safety net programs, all of which are compounded by environmental injustices. Further, studies conducted in the wake of the Dobbs decision find elevated stress levels among women of reproductive age. This may represent one pathway leading to adverse birth outcomes, as epidemiologic studies demonstrate that preterm birth rates increased following the 2016 election, a period of heightened stress. Reproductive and social policies are understudied contributors to adverse outcomes for reproductive-aged women and their children. This has important implications for maternal and child health equity, as those who will be the most impacted by reproductive and social policies already experience the highest rates of adverse birth outcomes and environmental toxicant exposure.

Pandemic Planning, Response, and Recovery for Pediatricians: A Focus on Health Equity and Social Determinants of Health

This article summarizes how pediatricians may be uniquely positioned to mitigate the long-term trajectory of COVID-19 on the health and wellness of pediatric patients especially with regard to screening for social determinants of health that are recognized drivers of disparate health outcomes. Health inequities, that is, disproportionately deleterious health outcomes that affect marginalized populations, have been a major source of vulnerability in past public health emergencies and natural disasters. Recommendations are provided for pediatricians to collaborate with disaster planning networks and lead strategies for public health communication and community engagement in pediatric pandemic and disaster planning, response, and recovery efforts.

Race, historical redlining, and contemporary transportation noise disparities in the United States

BACKGROUND

Legacies of discriminatory federal housing practices-e.g., racialized property appraisal by the Home Owners' Loan Corporation (HOLC) and institutionalized redlining by the Federal Housing Administration-include disparate present-day environmental health outcomes. Noise pollution is health-harming, but just one study has associated contemporary noise with redlining in some HOLC-mapped United States (US) cities, while two national studies found associations between greater neighborhood-level people of color composition and increased noise. No studies have examined noise pollution exposure disparities across all HOLC-mapped cities or based on the intersection of race/ethnicity and redlining.

OBJECTIVE

We address three objectives: (1) Assess disparities in fine-scale, per person transportation noise exposures by historical redlining status across all HOLC-mapped cities. (2) Quantify disparities in noise exposures by race/ethnicity nationwide. (3) Explore interactions between redlining status and race/ethnicity in noise exposures.

METHODS

We analyzed three data sources: (1) complete digital HOLC maps of ordered investment risk grades (A-D), (2) fine-scale (30 m) estimates of transportation noise levels (year-2020), and (3) sociodemographic characteristics of individuals in year-2020 census blocks.

RESULTS

We find an approximately monotonic association for excess transportation noise with HOLC grade, marked by a pronounced exposure increase (17.4 dBA or 3× loudness) between contemporary residents of grade A (highest-graded) and D (lowest-graded) neighborhoods, a pattern consistent across HOLC-mapped cities. People of color experience ~7 dBA greater (2× louder) excess transportation noise exposures than White people nationwide, a pattern consistent across US counties. Noise exposure disparities are larger by HOLC grade than by race/ethnicity. However, contemporary racial/ethnic noise exposure disparities persist within each HOLC grade at levels approximating those disparities existing in ungraded areas, indicating that historical redlining is one of multiple discriminatory practices shaping contemporary national soundscape injustices.

SIGNIFICANCE

Findings illustrate how historical redlining and broader racialized inequalities in US society have shaped environmental injustices nationwide.

IMPACT STATEMENT

Excessive noise exposures harm human health. Communities of color in the United States experience disparate noise exposures, although previous studies are limited by reliance upon aggregated data. They are also disproportionately concentrated in historically redlined areas. Legacies of redlining include persistent racial and economic inequalities and environmental health disparities. Here, we conduct the first complete national examination of contemporary noise pollution disparities with respect to historical redlining and race/ethnicity. Findings advance understanding of the historical roots and enduring salience of race-based disparities in noise pollution exposures and can inform efforts to address these disparities through noise pollution policy-making.

Environmental Justice and Systems Analysis for Air Quality Planning in the Port of Oakland in California

Many frontline communities experience adverse health impacts from living in proximity to high-polluting industrial sources. Securing environmental justice requires, in part, a comprehensive set of quantitative indicators. We incorporate environmental justice and life-cycle thinking into air quality planning to assess fine particulate matter (PM2.5) exposure and monetized damages from operating and maintaining the Port of Oakland, a major multimodal marine port located in the historically marginalized West Oakland community in the San Francisco Bay Area. The exposure domain for the assessment is the entire San Francisco Bay Area, a home to more than 7.5 million people. Of the more than 14 sources included in the emissions inventory, emissions from large container ships, or ocean-going vessels (OGVs), dominate the PM2.5 intake, and supply chain sources (material production and delivery, fuel production) represent between 3.5% and 7.5% of annual intake. Exposure damages, which model the costs from excess mortalities resulting from exposure from the study's emission sources, range from USD 100 to 270 million per annum. Variations in damages are due to the use of different concentration-response relationships, hazard ratios, and Port resurfacing area assumptions. Racial and income-based exposure disparities are stark. The Black population and people within the lowest income quintile are 2.2 and 1.9 times more disproportionately exposed, respectively, to the Port's pollution sources relative to the general population. Mitigation efforts focused on electrifying in-port trucking operations yield modest reductions (3.5%) compared to strategies that prioritize emission reductions from OGVs and commercial harbor craft operations (8.7-55%). Our recommendations emphasize that a systems-based approach is critical for identifying all relevant emission sources and mitigation strategies for improving equity in civil infrastructure systems.

Air quality and cancer risk in the All of Us Research Program

INTRODUCTION

The NIH All of Us Research Program has enrolled over 544,000 participants across the US with unprecedented racial/ethnic diversity, offering opportunities to investigate myriad exposures and diseases. This paper aims to investigate the association between PM2.5 exposure and cancer risks.

MATERIALS AND METHODS

This work was performed on data from 409,876 All of Us Research Program participants using the All of Us Researcher Workbench. Cancer case ascertainment was performed using data from electronic health records and the self-reported Personal Medical History questionnaire. PM2.5 exposure was retrieved from NASA's Earth Observing System Data and Information Center and assigned using participants' 3-digit zip code prefixes. Multivariate logistic regression was used to estimate the odds ratio (OR) and 95% confidence interval (CI). Generalized additive models (GAMs) were used to investigate non-linear relationships.

RESULTS

A total of 33,387 participants and 46,176 prevalent cancer cases were ascertained from participant EHR data, while 20,297 cases were ascertained from self-reported survey data from 18,133 participants; 9,502 cancer cases were captured in both the EHR and survey data. Average PM2.5 level from 2007 to 2016 was 8.90 μg/m3 (min 2.56, max 15.05). In analysis of cancer cases from EHR, an increased odds for breast cancer (OR 1.17, 95% CI 1.09-1.25), endometrial cancer (OR 1.33, 95% CI 1.09-1.62) and ovarian cancer (OR 1.20, 95% CI 1.01-1.42) in the 4th quartile of exposure compared to the 1st. In GAM, higher PM2.5 concentration was associated with increased odds for blood cancer, bone cancer, brain cancer, breast cancer, colon and rectum cancer, endocrine system cancer, lung cancer, pancreatic cancer, prostate cancer, and thyroid cancer.

CONCLUSIONS

We found evidence of an association of PM2.5 with breast, ovarian, and endometrial cancers. There is little to no prior evidence in the literature on the impact of PM2.5 on risk of these cancers, warranting further investigation.

Linking environmental injustices in Detroit, MI to institutional racial segregation through historical federal redlining

OBJECTIVES

To identify the most pervasive environmental exposures driving environmental disparities today associated with historical redlining in Detroit.

METHODS

We overlaid Detroit's 1939 Home Owners' Loan Corporation (HOLC) shapefile from the Mapping Inequality project onto the EPA EJScreen and the DOT National Transportation Noise maps to analyze differences in current demographic and environmental indicators between historically redlined (D-grade) and non-redlined neighborhoods using simple linear regression and a boosted classification tree algorithm.

RESULTS

Historically redlined neighborhoods in Detroit experienced significantly higher environmental hazards than non-redlined neighborhoods in the form of 12.1% (95% CI: 7.2-17.1%) higher levels of diesel particulate matter (PM), 32.2% (95% CI: 3.3-69.3%) larger traffic volumes, and 65.7% (95% CI: 8.6-152.8%) higher exposure to hazardous road noise (LEQ(24h) >70 dBA). Historically redlined neighborhoods were situated near 1.7-times (95% CI: 1.4-2.1) more hazardous waste sites and twice as many (95% CI: 1.5-2.7) risk management plan (RMP) sites than non-redlined neighborhoods. The lifetime cancer risk from inhalation of air toxics was 4.4% (95% CI: 2.9-6.6%) higher in historically redlined communities, and the risk of adverse respiratory health outcomes from air toxics was 3.9% (95% CI: 2.1-5.6%) higher. All factors considered together, among the environmental hazards considered, the most pervasive hazards in historically redlined communities are proximity to RMP sites, hazardous road noise, diesel PM, and cancer risk from air pollution.

CONCLUSIONS

Historically redlined neighborhoods may have a disproportionately higher risk of developing cancer and adverse respiratory health outcomes from air toxics. Policies targeting air and noise pollution from transportation sources, particularly from sources of diesel exhaust, in historically redlined neighborhoods may ameliorate some of the impacts of structural environmental racism from historical redlining in Detroit.

Association of Historical Housing Discrimination and Colon Cancer Treatment and Outcomes in the United States

PURPOSE

In the 1930s, the federally sponsored Home Owners' Loan Corporation (HOLC) used racial composition in its assessment of areas worthy of receiving loans. Neighborhoods with large proportions of Black residents were mapped in red (ie, redlining) and flagged as hazardous for mortgage financing. Redlining created a platform for systemic disinvestment in these neighborhoods, leading to barriers in access to resources that persist today. We investigated the association between residing in areas with different HOLC ratings and receipt of quality cancer care and outcomes among individuals diagnosed with colon cancer-a leading cause of cancer deaths amenable to early detection and treatment.

METHODS

Individuals who resided in zip code tabulation areas in 196 cities with HOLC rating and were diagnosed with colon cancer from 2007 to 2017 were identified from the National Cancer Database and assigned a HOLC grade (A, best; B, still desirable; C, definitely declining; and D, hazardous and mapped in red). Multivariable logistic regression models investigated association of area-level HOLC grade and late stage at diagnosis and receipt of guideline-concordant care. The product-limit method evaluated differences in time to adjuvant chemotherapy. Multivariable Cox proportional hazard models investigated differences in overall survival (OS).

RESULTS

There were 149,917 patients newly diagnosed with colon cancer with a median age of 68 years. Compared with people living in HOLC A areas, people living in HOLC D areas were more likely to be diagnosed with late-stage disease (adjusted odds ratio, 1.06 [95% CI, 1.00 to 1.12]). In addition, people living in HOLC B, C, and D areas had 8%, 16%, and 24% higher odds of not receiving guideline-concordant care, including lower receipt of surgery, evaluation of ≥12 lymph nodes, and chemotherapy. People residing in HOLC B, C, or D areas also experienced delays in initiation of adjuvant chemotherapy after surgery. People residing in HOLC C (adjusted hazard ratio [aHR], 1.09 [95% CI, 1.05 to 1.13]) and D (aHR, 1.13 [95% CI, 1.09 to 1.18]) areas had worse OS, including 13% and 20% excess risk of death for individuals diagnosed with early- and 6% and 8% for late-stage disease for HOLC C and D, respectively.

CONCLUSION

Historical housing discrimination is associated with worse contemporary access to colon cancer care and outcomes.

A US perspective on closing the carbon cycle to defossilize difficult-to-electrify segments of our economy

Electrification to reduce or eliminate greenhouse gas emissions is essential to mitigate climate change. However, a substantial portion of our manufacturing and transportation infrastructure will be difficult to electrify and/or will continue to use carbon as a key component, including areas in aviation, heavy-duty and marine transportation, and the chemical industry. In this Roadmap, we explore how multidisciplinary approaches will enable us to close the carbon cycle and create a circular economy by defossilizing these difficult-to-electrify areas and those that will continue to need carbon. We discuss two approaches for this: developing carbon alternatives and improving our ability to reuse carbon, enabled by separations. Furthermore, we posit that co-design and use-driven fundamental science are essential to reach aggressive greenhouse gas reduction targets.

Traffic-related air pollution in marginalized neighborhoods: a community perspective

OBJECTIVES

Marginalized communities are exposed to higher levels of traffic-related air pollution (TRAP) than the general population. TRAP exposure is linked to pulmonary toxicity, neurotoxicity, and cardiovascular toxicity often through mechanisms of inflammation and oxidative stress. Early life exposure to TRAP is also implicated in higher rates of asthma in these same communities. There is a critical need for additional epidemiological, in vivo, and in vitro studies to define the health risks of TRAP exposure affecting the most vulnerable groups to set strict, protective air pollution standards in these communities.

MATERIALS AND METHODS

A literature review was conducted to summarize recent findings (2010-2024) concerning TRAP exposure and toxic mechanisms that are relevant to the most affected underserved communities.

CONCLUSIONS

Guided by the perspectives of NYC community scientists, this contemporary review of toxicological and epidemiological studies considers how the exposome could lead to disproportionate exposures and health effects in underserved populations.

Historical Redlining and Heart Failure Outcomes Following Hospitalization in the Southeastern United States

BACKGROUND

Historical redlining, a discriminatory lending practice, is an understudied component of the patient risk environment following hospital discharge. We investigated associations between redlining, patient race, and outcomes following heart failure hospitalization.

METHODS AND RESULTS

We followed a hospital-based cohort of Black and White patients using electronic medical records for acute heart failure hospitalizations between 2010 and 2018 (n=6800). Patient residential census tracts were geocoded according to the 1930s Home Owners' Loan Corporation map grades (A/B: best/still desirable, C: declining, D: redlined). We used Poisson regression to analyze associations between Home Owners' Loan Corporation grade and 30-day outcomes (readmissions, mortality, and their composite). One-third of patients resided in historically redlined tracts (n=2034). In race-stratified analyses, there was a positive association between historically declining neighborhoods and composite readmissions and mortality for Black patients (risk ratio [RR], 1.24 [95% CI, 1.003-1.54]) and an inverse association between redlined neighborhoods and 30-day readmissions among White patients (RR, 0.58 [95% CI, 0.39-0.86]). Examining racial disparities across Home Owners' Loan Corporation grades, Black patients had higher 30-day readmissions (RR, 1.86 [95% CI, 1.31-2.65]) and composite readmissions and mortality (RR, 1.32 [95% CI, 1.04-1.65]) only in historically redlined neighborhoods.

CONCLUSIONS

Historical redlining had potentially mixed impacts on outcomes by race, such that residing in less desirable neighborhoods was associated with an elevated risk of an adverse outcome following heart failure hospitalization in Black patients and a reduced risk in White patients. Moreover, racial disparities in patient outcomes were present only in historically redlined neighborhoods. Additional research is needed to explore observed heterogeneity in outcomes.

A review of air pollution as a driver of cardiovascular disease risk across the diabetes spectrum

The prevalence of diabetes is estimated to reach almost 630 million cases worldwide by the year 2045; of current and projected cases, over 90% are type 2 diabetes. Air pollution exposure has been implicated in the onset and progression of diabetes. Increased exposure to fine particulate matter air pollution (PM2.5) is associated with increases in blood glucose and glycated hemoglobin (HbA1c) across the glycemic spectrum, including normoglycemia, prediabetes, and all forms of diabetes. Air pollution exposure is a driver of cardiovascular disease onset and exacerbation and can increase cardiovascular risk among those with diabetes. In this review, we summarize the literature describing the relationships between air pollution exposure, diabetes and cardiovascular disease, highlighting how airborne pollutants can disrupt glucose homeostasis. We discuss how air pollution and diabetes, via shared mechanisms leading to endothelial dysfunction, drive increased cardiovascular disease risk. We identify portable air cleaners as potentially useful tools to prevent adverse cardiovascular outcomes due to air pollution exposure across the diabetes spectrum, while emphasizing the need for further study in this particular population. Given the enormity of the health and financial impacts of air pollution exposure on patients with diabetes, a greater understanding of the interventions to reduce cardiovascular risk in this population is needed.

Beyond traffic jam alleviation: evaluating the health and health equity impacts of New York City's congestion pricing plan

New York City (NYC) is slated to be the first jurisdiction in the USA to implement a cordon-based congestion tax, which will be levied on vehicles entering its Central Business District. Several cities around the world, for example, London and Stockholm, have had similar cordon-based pricing programmes, defined as road pricing that charges drivers a fee for entering a specified area (typically a congested urban centre). In addition to reducing congestion and creating revenue, projections suggest the NYC congestion pricing plan may yield meaningful traffic-related air quality improvements that could result in health benefits. NYC is a large city with high air pollution and substantial racial/ethnic and socioeconomic health inequities. The distinct geography and meteorological conditions of the city also suggest that the policy's impact on air quality may extend beyond the NYC metropolitan area. As such, the potential breadth, directionality and magnitude of health impacts on communities who might be heavily affected by the nation's first congestion pricing plan should be empirically investigated. We briefly review evaluation studies of other cordon-based congestion pricing policies and argue that implementation of this policy provides an excellent opportunity to employ a quasi-experimental study design to evaluate the policy's impacts on air quality and health outcomes across population subgroups using a health equity lens. We discuss why real-time evaluations of the NYC congestion pricing plan can potentially help optimise benefits for communities historically negatively affected by traffic-related air pollution. Assessing intended and unintended impacts on health equity is key to achieving these goals.

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.

Air Pollution Inequality in the Denver Metroplex and its Relationship to Historical Redlining

Prior studies have shown that people of color (POC) in the United States are exposed to higher levels of pollution than non-Hispanic White people. We show that the city of Denver, Colorado, displays similar race- and ethnicity-based air pollution disparities by using a combination of high-resolution satellite data, air pollution modeling, historical demographic information, and areal apportionment techniques. TROPOMI NO2 columns and modeled PM2.5 concentrations from 2019 are higher in communities subject to redlining. We calculated and compared Spearman coefficients for pollutants and race at the census tract level for every city that underwent redlining to contextualize the disparities in Denver. We find that the location of polluting infrastructure leads to higher populations of POC living near point sources, including 40% higher Hispanic and Latino populations. This influences pollution distribution, with annual average PM2.5 surface concentrations of 6.5 μg m-3 in census tracts with 0-5% Hispanic and Latino populations and 7.5 μg m-3 in census tracts with 60-65% Hispanic and Latino populations. Traffic analysis and emission inventory data show that POC are more likely to live near busy highways. Unequal spatial distribution of pollution sources and POC have allowed for pollution disparities to persist despite attempts by the city to rectify them. Finally, we identify the core causes of the pollution disparities to provide direction for remediation.

Increasing Racial and Ethnic Disparities in Ambient Air Pollution-Attributable Morbidity and Mortality in the United States

BACKGROUND

Ambient nitrogen dioxide (NO 2 ) and fine particulate matter with aerodynamic diameter ≤ 2.5 μ m (PM 2.5 ) threaten public health in the US, and systemic racism has led to modern-day disparities in the distribution and associated health impacts of these pollutants.

OBJECTIVES

Many studies on environmental injustices related to ambient air pollution focus only on disparities in pollutant concentrations or provide only an assessment of pollution or health disparities at a snapshot in time. In this study, we compare injustices in NO 2 - and PM 2.5 -attributable health burdens, considering NO 2 -attributable health impacts across the entire US; document changing disparities in these health burdens over time (2010-2019); and evaluate how more stringent air quality standards would reduce disparities in health impacts associated with these pollutants.

METHODS

Through a health impact assessment, we quantified census tract-level variations in health outcomes attributable to NO 2 and PM 2.5 using health impact functions that combine demographic data from the US Census Bureau; two spatially resolved pollutant datasets, which fuse satellite data with physical and statistical models; and epidemiologically derived relative risk estimates and incidence rates from the Global Burden of Disease study.

RESULTS

Despite overall decreases in the public health damages associated with NO 2 and PM 2.5 , racial and ethnic relative disparities in NO 2 -attributable pediatric asthma and PM 2.5 -attributable premature mortality have widened in the US during the last decade. Racial relative disparities in PM 2.5 -attributable premature mortality and NO 2 -attributable pediatric asthma have increased by 16% and 19%, respectively, between 2010 and 2019. Similarly, ethnic relative disparities in PM 2.5 -attributable premature mortality have increased by 40% and NO 2 -attributable pediatric asthma by 10%.

DISCUSSION

Enacting and attaining more stringent air quality standards for both pollutants could preferentially benefit the most marginalized and minoritized communities by greatly reducing racial and ethnic relative disparities in pollution-attributable health burdens in the US. Our methods provide a semi-observational approach to track changes in disparities in air pollution and associated health burdens across the US. https://doi.org/10.1289/EHP11900.

Trying to Do What's Best: Maternal Perspectives About Toddler Sleep Health Among an Underresourced Sample of Mothers With Diverse Racial and Ethnic Identities

INTRODUCTION

This study describes mothers' knowledge, attitudes, beliefs, and practices about their toddler's sleep health among an underresourced sample of mothers with diverse racial and ethnic identities.

METHOD

This was a descriptive qualitative study with 16 mothers and their 12- to 36-month-old child. Mothers completed a semistructured, audio-recorded interview about their toddler's sleep health. Data were analyzed using inductive content analysis on the basis of established methods.

RESULTS

Mothers self-identified as 18.8% Black, 43.8% White, 12.5% multiracial, 25.0% other race, and 37.5% Hispanic. Of the mothers, 80.0% reported a past year household income of ≤ $40,000. A core construct, "Trying to do What's Best," emerged from the interview data, and this construct included three domains: Getting Good Sleep, Getting Thrown Off, and Rolling With It.

DISCUSSION

Findings support future strengths-based and multilevel sleep health-promoting interventions.

Indoor Air Sources of Outdoor Air Pollution: Health Consequences, Policy, and Recommendations: An Official American Thoracic Society Workshop Report

Indoor sources of air pollution worsen indoor and outdoor air quality. Thus, identifying and reducing indoor pollutant sources would decrease both indoor and outdoor air pollution, benefit public health, and help address the climate crisis. As outdoor sources come under regulatory control, unregulated indoor sources become a rising percentage of the problem. This American Thoracic Society workshop was convened in 2022 to evaluate this increasing proportion of indoor contributions to outdoor air quality. The workshop was conducted by physicians and scientists, including atmospheric and aerosol scientists, environmental engineers, toxicologists, epidemiologists, regulatory policy experts, and pediatric and adult pulmonologists. Presentations and discussion sessions were centered on 1) the generation and migration of pollutants from indoors to outdoors, 2) the sources and circumstances representing the greatest threat, and 3) effective remedies to reduce the health burden of indoor sources of air pollution. The scope of the workshop was residential and commercial sources of indoor air pollution in the United States. Topics included wood burning, natural gas, cooking, evaporative volatile organic compounds, source apportionment, and regulatory policy. The workshop concluded that indoor sources of air pollution are significant contributors to outdoor air quality and that source control and filtration are the most effective measures to reduce indoor contributions to outdoor air. Interventions should prioritize environmental justice: Households of lower socioeconomic status have higher concentrations of indoor air pollutants from both indoor and outdoor sources. We identify research priorities, potential health benefits, and mitigation actions to consider (e.g., switching from natural gas to electric stoves and transitioning to scent-free consumer products). The workshop committee emphasizes the benefits of combustion-free homes and businesses and recommends economic, legislative, and education strategies aimed at achieving this goal.

Composition of indoor organic surface films in residences: simulating the influence of sources, partitioning, particle deposition, and air exchange

Indoor surfaces are coated with organic films that modulate thermodynamic interactions between the surfaces and room air. Recently published models can simulate film formation and growth via gas-surface partitioning, but none have statistically investigated film composition. The Indoor Model of Aerosols, Gases, Emissions, and Surfaces (IMAGES) was used here to simulate ten years of nonreactive film growth upon impervious indoor surfaces within a Monte Carlo procedure representing a sub-set of North American residential buildings. Film composition was resolved into categories reflecting indoor aerosol (gas + particle phases) factors from three sources: outdoor-originating, indoor-emitted, and indoor-generated secondary organic material. In addition to gas-to-film partitioning, particle deposition was modeled as a vector for organics to enter films, and it was responsible for a majority of the film mass after ∼1000 days of growth for the median simulation and is likely the main source of LVOCs within films. Therefore, the organic aerosol factor possessing the most SVOCs contributes most strongly to the composition of early films, but as the film ages, films become more dominated by the factor with the highest particle concentration. Indoor-emitted organics (e.g. from cooking) often constituted at least a plurality of the simulated mass in developed films, but indoor environments are diverse enough that any major organic material source could be the majority contributor to film mass, depending on building characteristics and indoor activities. A sensitivity analysis suggests that rapid film growth is most likely in both newer, more air-tight homes and older homes near primary pollution sources.

Measuring long-term exposure to wildfire PM2.5 in California: Time-varying inequities in environmental burden

Wildfires have become more frequent and intense due to climate change and outdoor wildfire fine particulate matter (PM2.5) concentrations differ from relatively smoothly varying total PM2.5. Thus, we introduced a conceptual model for computing long-term wildfire PM2.5 and assessed disproportionate exposures among marginalized communities. We used monitoring data and statistical techniques to characterize annual wildfire PM2.5 exposure based on intermittent and extreme daily wildfire PM2.5 concentrations in California census tracts (2006 to 2020). Metrics included: 1) weeks with wildfire PM2.5 < 5 μg/m3; 2) days with non-zero wildfire PM2.5; 3) mean wildfire PM2.5 during peak exposure week; 4) smoke waves (≥2 consecutive days with <15 μg/m3 wildfire PM2.5); and 5) mean annual wildfire PM2.5 concentration. We classified tracts by their racial/ethnic composition and CalEnviroScreen (CES) score, an environmental and social vulnerability composite measure. We examined associations of CES and racial/ethnic composition with the wildfire PM2.5 metrics using mixed-effects models. Averaged 2006 to 2020, we detected little difference in exposure by CES score or racial/ethnic composition, except for non-Hispanic American Indian and Alaska Native populations, where a 1-SD increase was associated with higher exposure for 4/5 metrics. CES or racial/ethnic × year interaction term models revealed exposure disparities in some years. Compared to their California-wide representation, the exposed populations of non-Hispanic American Indian and Alaska Native (1.68×, 95% CI: 1.01 to 2.81), white (1.13×, 95% CI: 0.99 to 1.32), and multiracial (1.06×, 95% CI: 0.97 to 1.23) people were over-represented from 2006 to 2020. In conclusion, during our study period in California, we detected disproportionate long-term wildfire PM2.5 exposure for several racial/ethnic groups.

Historical Redlining Is Associated with Disparities in Environmental Quality across California

Historical policies have been shown to underpin environmental quality. In the 1930s, the federal Home Owners' Loan Corporation (HOLC) developed the most comprehensive archive of neighborhoods that would have been redlined by local lenders and the Federal Housing Administration, often applying racist criteria. Our study explored how redlining is associated with environmental quality across eight California cities. We integrated HOLC's graded maps [grades A (i.e., "best" and "greenlined"), B, C, and D (i.e., "hazardous" and "redlined")] with 10 environmental hazards using data from 2018 to 2021 to quantify the spatial overlap among redlined neighborhoods and environmental hazards. We found that formerly redlined neighborhoods have poorer environmental quality relative to those of other HOLC grades via higher pollution, more noise, less vegetation, and elevated temperatures. Additionally, we found that intraurban disparities were consistently worse for formerly redlined neighborhoods across environmental hazards, with redlined neighborhoods having higher pollution burdens (77% of redlined neighborhoods vs 18% of greenlined neighborhoods), more noise (72% vs 18%), less vegetation (86% vs 12%), and elevated temperature (72% vs 20%), than their respective city's average. Our findings highlight that redlining, a policy abolished in 1968, remains an environmental justice concern by shaping the environmental quality of Californian urban neighborhoods.

Modification of the PM2.5- and extreme heat-mortality relationships by historical redlining: a case-crossover study in thirteen U.S. states

BACKGROUND

Redlining has been associated with worse health outcomes and various environmental disparities, separately, but little is known of the interaction between these two factors, if any. We aimed to estimate whether living in a historically-redlined area modifies the effects of exposures to ambient PM2.5 and extreme heat on mortality by non-external causes.

METHODS

We merged 8,884,733 adult mortality records from thirteen state departments of public health with scanned and georeferenced Home Owners Loan Corporation (HOLC) maps from the University of Richmond, daily average PM2.5 from a sophisticated prediction model on a 1-km grid, and daily temperature and vapor pressure from the Daymet V4 1-km grid. A case-crossover approach was used to assess modification of the effects of ambient PM2.5 and extreme heat exposures by redlining and control for all fixed and slow-varying factors by design. Multiple moving averages of PM2.5 and duration-aware analyses of extreme heat were used to assess the most vulnerable time windows.

RESULTS

We found significant statistical interactions between living in a redlined area and exposures to both ambient PM2.5 and extreme heat. Individuals who lived in redlined areas had an interaction odds ratio for mortality of 1.0093 (95% confidence interval [CI]: 1.0084, 1.0101) for each 10 µg m-3 increase in same-day ambient PM2.5 compared to individuals who did not live in redlined areas. For extreme heat, the interaction odds ratio was 1.0218 (95% CI 1.0031, 1.0408).

CONCLUSIONS

Living in areas that were historically-redlined in the 1930's increases the effects of exposures to both PM2.5 and extreme heat on mortality by non-external causes, suggesting that interventions to reduce environmental health disparities can be more effective by also considering the social context of an area and how to reduce disparities there. Further study is required to ascertain the specific pathways through which this effect modification operates and to develop interventions that can contribute to health equity for individuals living in these areas.

Addressing Structural Racism Through Public Policy Advocacy: A Policy Statement From the American Heart Association

During the COVID-19 pandemic, the American Heart Association created a new 2024 Impact Goal with health equity at its core, in recognition of the increasing health disparities in our country and the overwhelming evidence of the damaging effect of structural racism on cardiovascular and stroke health. Concurrent with the announcement of the new Impact Goal was the release of an American Heart Association presidential advisory on structural racism, recognizing racism as a fundamental driver of health disparities and directing the American Heart Association to advance antiracist strategies regarding science, business operations, leadership, quality improvement, and advocacy. This policy statement builds on the call to action put forth in our presidential advisory, discussing specific opportunities to leverage public policy in promoting overall well-being and rectifying those long-standing structural barriers that impede the progress that we need and seek for the health of all communities. Although this policy statement discusses difficult aspects of our past, it is meant to provide a forward-looking blueprint that can be embraced by a broad spectrum of stakeholders who share the association's commitment to addressing structural racism and realizing true health equity.

Spatial Patterning of Spontaneous and Medically Indicated Preterm Birth in Philadelphia

Preterm birth (PTB) remains a key public health issue that disproportionately affects Black individuals. Since spontaneous PTB (sPTB) and medically indicated PTB (mPTB) may have different causes and interventions, we quantified racial disparities for sPTB and mPTB, and we characterized the geographic patterning of these phenotypes, overall and according to race/ethnicity. We examined a pregnancy cohort of 83,952 singleton births at 2 Philadelphia hospitals from 2008-2020, and classified each PTB as sPTB or mPTB. We used binomial regression to quantify the magnitude of racial disparities between non-Hispanic Black and non-Hispanic White individuals, then generated small area estimates by applying a Bayesian model that accounts for small numbers and smooths estimates of PTB risk by borrowing information from neighboring areas. Racial disparities in both sPTB and mPTB were significant (relative risk of sPTB = 1.83, 95% confidence interval: 1.70, 1.98; relative risk of mPTB = 2.20, 95% confidence interval: 2.00, 2.42). The disparity was 20% greater in mPTB than sPTB. There was substantial geographic variation in PTB, sPTB, and mPTB risks and racial disparity. Our findings underscore the importance of distinguishing PTB phenotypes within the context of public health and preventive medicine. Future work should consider social and environmental exposures that may explain geographic differences in PTB risk and disparities.

Organized abandonment under racial capitalism: Measuring accountable actors of structural racism for public health research and action

Understanding the shifting nature of structural racism historically and across institutions is vital for effective action towards racial health equity. While public health research on structural racism is rapidly increasing, most studies are missing the interdependence of policies and institutional practices over time that shape power imbalances and lead to entrenched health inequities. Here, we discuss Ruth Wilson Gilmore's concept of organized abandonment - the intentional disinvestment in communities which, in turn, creates opportunities for extraction, revenue generation, and carceral enforcement to fill the cracks of a compromised social infrastructure - to encourage action-oriented public health research that is grounded in history and an understanding of racial capitalism. We present a case example using publicly-available data on redlining, gentrification and policing in Seattle, Washington. We mapped the intersections of redlining and gentrification and estimated their neighborhood-level association with police activity using Bayesian spatial Poisson regression models. We found that histories of racist housing policies like redlining and processes of gentrification are interdependent and shape contemporary neighborhood racial and economic segregation and police activity. Compared to structurally advantaged neighborhoods, police stops were higher in neighborhoods that were 1) historically disinvested (i.e. redlined) and remain low-income and structurally disadvantaged and 2) formerly industrial and business districts that were not redlined and are now gentrified. Notably, we found that policing practices were significantly more intensive in neighborhoods that were both high redlined and gentrified. Together, these findings illustrate how the place-based racialized processes of dispossession, displacement and policing are deeply intertwined to maintain racial capitalism. Our findings also highlight the importance of examining multiple racialized processes simultaneously to fill critical gaps in the existing literature that are necessary for sustainable solutions to address structural racism.

Impact of socioeconomic factors on allergic diseases

Allergic and immunologic conditions, including asthma, food allergy, atopic dermatitis, and allergic rhinitis, are among the most common chronic conditions in children and adolescents that often last into adulthood. Although rare, inborn errors of immunity are life-altering and potentially fatal if unrecognized or untreated. Thus, allergic and immunologic conditions are both medical and public health issues that are profoundly affected by socioeconomic factors. Recently, studies have highlighted societal issues to evaluate factors at multiple levels that contribute to health inequities and the potential steps toward closing those gaps. Socioeconomic disparities can influence all aspects of care, including health care access and quality, diagnosis, management, education, and disease prevalence and outcomes. Ongoing research, engagement, and deliberate investment of resources by relevant stakeholders and advocacy approaches are needed to identify and address the impact of socioeconomics on health care disparities and outcomes among patients with allergic and immunologic diseases.

Racial and ethnic inequities in stillbirth in the US: Looking upstream to close the gap: Seminars in Perinatology

Though stillbirth rates in the United States improved over the previous decades, inequities in stillbirth by race and ethnicity have persisted nearly unchanged since data collection began. Black and Indigenous pregnant people face a two-fold greater risk of experiencing the devastating consequences of stillbirth compared to their White counterparts. Because race is a social rather than biological construct, inequities in stillbirth rates are a downstream consequence of structural, institutional, and interpersonal racism which shape a landscape of differential access to opportunities for health. These downstream consequences can include differences in the prevalence of chronic health conditions as well as structural differences in the quality of health care or healthy neighborhood conditions, each of which likely plays a role in racial and ethnic inequities in stillbirth. Research and intervention approaches that utilize an equity lens may identify ways to close gaps in stillbirth incidence or in responding to the health and socioemotional consequences of stillbirth. A community-engaged approach that incorporates experiential wisdom will be necessary to create a full picture of the causes and consequences of inequity in stillbirth outcomes. Investigators working in tandem with community partners, utilizing a combination of qualitative, quantitative, and implementation science approaches, may more fully elucidate the underpinnings of racial and ethnic inequities in stillbirth outcomes.

Building towards an adolescent neural urbanome: Expanding environmental measures using linked external data (LED) in the ABCD study

Many recent studies have demonstrated that environmental contexts, both social and physical, have an important impact on child and adolescent neural and behavioral development. The adoption of geospatial methods, such as in the Adolescent Brain Cognitive Development (ABCD) Study, has facilitated the exploration of many environmental contexts surrounding participants' residential locations without creating additional burdens for research participants (i.e., youth and families) in neuroscience studies. However, as the number of linked databases increases, developing a framework that considers the various domains related to child and adolescent environments external to their home becomes crucial. Such a framework needs to identify structural contextual factors that may yield inequalities in children's built and natural environments; these differences may, in turn, result in downstream negative effects on children from historically minoritized groups. In this paper, we develop such a framework - which we describe as the "adolescent neural urbanome" - and use it to categorize newly geocoded information incorporated into the ABCD Study by the Linked External Data (LED) Environment & Policy Working Group. We also highlight important relationships between the linked measures and describe possible applications of the Adolescent Neural Urbanome. Finally, we provide a number of recommendations and considerations regarding the responsible use and communication of these data, highlighting the potential harm to historically minoritized groups through their misuse.

Short-Term Increases in NO2 and O3 Concentrations during Pregnancy and Stillbirth Risk in the U.S.: A Time-Stratified Case-Crossover Study

Associations between gaseous pollutant exposure and stillbirth have focused on exposures averaged over trimesters or gestation. We investigated the association between short-term increases in nitrogen dioxide (NO2) and ozone (O3) concentrations and stillbirth risk among a national sample of 116 788 Medicaid enrollees from 2000 to 2014. A time-stratified case-crossover design was used to estimate distributed (lag 0-lag 6) and cumulative lag effects, which were adjusted for PM2.5 concentration and temperature. Effect modification by race/ethnicity and proximity to hydraulic fracturing (fracking) wells was assessed. Short-term increases in the NO2 and O3 concentrations were not associated with stillbirth in the overall sample. Among American Indian individuals (n = 1694), a 10 ppb increase in NO2 concentrations was associated with increased stillbirth odds at lag 0 (5.66%, 95%CI: [0.57%, 11.01%], p = 0.03) and lag 1 (4.08%, 95%CI: [0.22%, 8.09%], p = 0.04) but not lag 0-6 (7.12%, 95%CI: [-9.83%, 27.27%], p = 0.43). Among participants living in zip codes within 15 km of active fracking wells (n = 9486), a 10 ppb increase in NO2 concentration was associated with increased stillbirth odds in single-day lags (2.42%, 95%CI: [0.37%, 4.52%], p = 0.02 for lag 0 and 1.83%, 95%CI: [0.25%, 3.43%], p = 0.03 for lag 1) but not the cumulative lag (lag 0-6) (4.62%, 95%CI: [-2.75%, 12.55%], p = 0.22). Odds ratios were close to the null in zip codes distant from fracking wells. Future studies should investigate the role of air pollutants emitted from fracking and potential racial disparities in the relationship between short-term increases in NO2 concentrations and stillbirth.

Integrating Clinical and Air Quality Data to Improve Prediction of COPD Exacerbations

Several studies have found associations between air pollution and respiratory disease outcomes. However, there is minimal prognostic research exploring whether integrating air quality into clinical prediction models can improve accuracy and utility. In this study, we built models using both logistic regression and random forests to determine the benefits of including air quality data with meteorological and clinical data in prediction of COPD exacerbations requiring medical care. Logistic models were not improved by inclusion of air quality. However, the net benefit curves of random forest models showed greater clinical utility with the addition of air quality data. These models demonstrate a practical and relatively low-cost way to include environmental information into clinical prediction tools to improve the clinical utility of COPD prediction. Findings could be used to provide population level health warnings as well as individual-patient risk assessments.

Ambient fine particulate matter and breast cancer incidence in a large prospective US cohort

BACKGROUND

Fine particulate matter (PM2.5) has been inconsistently associated with breast cancer incidence, however, few studies have considered historic exposure when levels were higher.

METHODS

Outdoor residential PM2.5 concentrations were estimated using a nationwide spatiotemporal model for women in the National Institutes of Health-AARP Diet and Health Study, a prospective cohort located in 6 states (California, Florida, Louisiana, New Jersey, North Carolina, and Pennsylvania) and 2 metropolitan areas (Atlanta, GA, and Detroit, MI) and enrolled in 1995-1996 (n = 196 905). Annual average PM2.5 concentrations were estimated for a 5-year historical period 10 years prior to enrollment (1980-1984). We used Cox regression to estimate adjusted hazard ratios (HRs) and 95% confidence intervals (CIs) for the association between a 10 µg/m3 increase in PM2.5 and breast cancer incidence overall and by estrogen receptor status and catchment area.

RESULTS

With follow-up of participants through 2017, a total of 15 870 breast cancer cases were identified. A 10 ug/m3 increase in PM2.5 was statistically significantly associated with overall breast cancer incidence (HR = 1.08, 95% CI = 1.02 to 1.13). The association was evident for estrogen receptor-positive (HR = 1.10, 95% CI = 1.04 to 1.17) but not estrogen receptor-negative tumors (HR = 0.97, 95% CI = 0.84 to 1.13; Pheterogeneity = .3). Overall breast cancer hazard ratios were more than 1 across the catchment areas, ranging from a hazard ratio of 1.26 (95% CI = 0.96 to 1.64) for North Carolina to a hazard ratio of 1.04 (95% CI = 0.68 to 1.57) for Louisiana (Pheterogeneity = .9).

CONCLUSIONS

In this large US cohort with historical air pollutant exposure estimates, PM2.5 was associated with risk of estrogen receptor-positive breast cancer. State-specific estimates were imprecise but suggest that future work should consider region-specific associations and the potential contribution of PM2.5 chemical constituency in modifying the observed association.

Concurrent Heat and Air Pollution Exposures among People Experiencing Homelessness

BACKGROUND

Extreme heat and air pollution are important human health concerns; exposure can affect mental and physical well-being, particularly during periods of co-occurrence. Yet, the impacts on people are largely determined by underlying health conditions, coupled with the length and intensity of exposure. Preexisting adverse health conditions and prolonged exposure times are more common for people experiencing homelessness, particularly those with intersectional identity characteristics (e.g., disease, ability, age, etc.). Partially due to methodological limitations, such as data scarcity, there is a lack of research at the intersection of this at-risk population within the climate-health domain.

OBJECTIVES

We have three distinct objectives throughout this article: a) to advance critical discussions around the state of concurrent high heat and air pollution exposure research as it relates to people experiencing homelessness; b) to assert the importance of heat and air pollution exposure research among a highly vulnerable, too-often homogenized population-people experiencing homelessness; and c) to underline challenges in this area of study while presenting potential ways to address such shortcomings.

DISCUSSION

The health insights from concurrent air pollution and heat exposure studies are consequential when studying unhoused communities who are already overexposed to harmful environmental conditions. Without holistic data sets and more advanced methods to study concurrent exposures, appropriate and targeted prevention and intervention strategies cannot be developed to protect this at-risk population. We highlight that a) concurrent high heat and air pollution exposure research among people experiencing homelessness is significantly underdeveloped considering the pressing human health implications; b) the severity of physiological responses elicited by high heat and air pollution are predicated on exposure intensity and time, and thus people without means of seeking climate-controlled shelter are most at risk; and c) collaboration among transdisciplinary teams is needed to resolve data resolution issues and enable targeted prevention and intervention strategies. https://doi.org/10.1289/EHP13402.

Broadening the Environmental Lens to Include Social and Structural Determinants of Women's Health Disparities

BACKGROUND

Due to the physical, metabolic, and hormonal changes before, during, and after pregnancy, women-defined here as people assigned female at birth-are particularly susceptible to environmental insults. Racism, a driving force of social determinants of health, exacerbates this susceptibility by affecting exposure to both chemical and nonchemical stressors to create women's health disparities.

OBJECTIVES

To better understand and address social and structural determinants of women's health disparities, the National Institute of Environmental Health Sciences (NIEHS) hosted a workshop focused on the environmental impacts on women's health disparities and reproductive health in April 2022. This commentary summarizes foundational research and unique insights shared by workshop participants, who emphasized the need to broaden the definition of the environment to include upstream social and structural determinants of health. We also summarize current challenges and recommendations, as discussed by workshop participants, to address women's environmental and reproductive health disparities.

DISCUSSION

The challenges related to women's health equity, as identified by workshop attendees, included developing research approaches to better capture the social and structural environment in both human and animal studies, integrating environmental health principles into clinical care, and implementing more inclusive publishing and funding approaches. Workshop participants discussed recommendations in each of these areas that encourage interdisciplinary collaboration among researchers, clinicians, funders, publishers, and community members. https://doi.org/10.1289/EHP12996.

Local exposure misclassification in national models: relationships with urban infrastructure and demographics

BACKGROUND

National-scale linear regression-based modeling may mischaracterize localized patterns, including hyperlocal peaks and neighborhood- to regional-scale gradients. For studies focused on within-city differences, this mischaracterization poses a risk of exposure misclassification, affecting epidemiological and environmental justice conclusions.

OBJECTIVE

Characterize the difference between intraurban pollution patterns predicted by national-scale land use regression modeling and observation-based estimates within a localized domain and examine the relationship between that difference and urban infrastructure and demographics.

METHODS

We compare highly resolved (0.01 km2) observations of NO2 mixing ratio and ultrafine particle (UFP) count obtained via mobile monitoring with national model predictions in thirteen neighborhoods in the San Francisco Bay Area. Grid cell-level divergence between modeled and observed concentrations is termed "localized difference." We use a flexible machine learning modeling technique, Bayesian Additive Regression Trees, to investigate potentially nonlinear relationships between discrepancy between localized difference and known local emission sources as well as census block group racial/ethnic composition.

RESULTS

We find that observed local pollution extremes are not represented by land use regression predictions and that observed UFP count significantly exceeds regression predictions. Machine learning models show significant nonlinear relationships among localized differences between predictions and observations and the density of several types of pollution-related infrastructure (roadways, commercial and industrial operations). In addition, localized difference was greater in areas with higher population density and a lower share of white non-Hispanic residents, indicating that exposure misclassification by national models differs among subpopulations.

IMPACT

Comparing national-scale pollution predictions with hyperlocal observations in the San Francisco Bay Area, we find greater discrepancies near major roadways and food service locations and systematic underestimation of concentrations in neighborhoods with a lower share of non-Hispanic white residents. These findings carry implications for using national-scale models in intraurban epidemiological and environmental justice applications and establish the potential utility of supplementing large-scale estimates with publicly available urban infrastructure and pollution source information.

Ethnoracial Disparities in Nitrogen Dioxide Pollution in the United States: Comparing Data Sets from Satellites, Models, and Monitors

In the United States (U.S.), studies on nitrogen dioxide (NO2) trends and pollution-attributable health effects have historically used measurements from in situ monitors, which have limited geographical coverage and leave 66% of urban areas unmonitored. Novel tools, including remotely sensed NO2 measurements and estimates of NO2 estimates from land-use regression and photochemical models, can aid in assessing NO2 exposure gradients, leveraging their complete spatial coverage. Using these data sets, we find that Black, Hispanic, Asian, and multiracial populations experience NO2 levels 15-50% higher than the national average in 2019, whereas the non-Hispanic White population is consistently exposed to levels that are 5-15% lower than the national average. By contrast, the in situ monitoring network indicates more moderate ethnoracial NO2 disparities and different rankings of the least- to most-exposed ethnoracial population subgroup. Validating these spatially complete data sets against in situ observations reveals similar performance, indicating that all these data sets can be used to understand spatial variations in NO2. Integrating in situ monitoring, satellite data, statistical models, and photochemical models can provide a semiobservational record, complete geospatial coverage, and increasingly high spatial resolution, enhancing future efforts to characterize, map, and track exposure and inequality for highly spatially heterogeneous pollutants like NO2.

Climate change as a threat multiplier to environmental reproductive justice

Legacies of racial capitalism and colonialism drive present day racial disparities in perinatal health outcomes. Climate change amplifies existing social inequalities associated with environmental exposures and reproductive health, of which BIPOC (Black, Indigenous, and people of color) communities bear a disproportionate burden. Through case studies, this article summarizes three examples of climate justice issues with reproductive healthcare outcomes: traffic related air pollution exposure, chemical exposures in personal care products and plastics, and natural disaster frequency. We advocate for incorporation of climate justice and environmental health impact into medical school curriculum, increased prenatal screening for environmental toxins, and physician engagement with local environmental issues.

The Epidemiology of Violence Exposure in Children

Exposure to violence remains a significant issue for children in the United States. The COVID-19 pandemic exacerbated many of these exposures. Violence unequally impacts children of color and lesbian, gay, bisexual, transgender, and questioning youth. Pediatricians can and must continue to advocate and intervene to decrease pediatric violence exposure and its effects.

Emergency department visits associated with wildfire smoke events in California, 2016-2019

Wildfire smoke has been associated with adverse respiratory outcomes, but the impacts of wildfire on other health outcomes and sensitive subpopulations are not fully understood. We examined associations between smoke events and emergency department visits (EDVs) for respiratory, cardiovascular, diabetes, and mental health outcomes in California during the wildfire season June-December 2016-2019. Daily, zip code tabulation area-level wildfire-specific fine particulate matter (PM2.5) concentrations were aggregated to air basins. A "smoke event" was defined as an air basin-day with a wildfire-specific PM2.5 concentration at or above the 98th percentile across all air basin-days (threshold = 13.5 μg/m3). We conducted a two-stage time-series analysis using quasi-Poisson regression considering lag effects and random effects meta-analysis. We also conducted analyses stratified by race/ethnicity, age, and sex to assess potential effect modification. Smoke events were associated with an increased risk of EDVs for all respiratory diseases at lag 1 [14.4%, 95% confidence interval (CI): (6.8, 22.5)], asthma at lag 0 [57.1% (44.5, 70.8)], and chronic lower respiratory disease at lag 0 [12.7% (6.2, 19.6)]. We also found positive associations with EDVs for all cardiovascular diseases at lag 10. Mixed results were observed for mental health outcomes. Stratified results revealed potential disparities by race/ethnicity. Short-term exposure to smoke events was associated with increased respiratory and schizophrenia EDVs. Cardiovascular impacts may be delayed compared to respiratory outcomes.

State-of-the-Science Data and Methods Need to Guide Place-Based Efforts to Reduce Air Pollution Inequity

BACKGROUND

Recently enacted environmental justice policies in the United States at the state and federal level emphasize addressing place-based inequities, including persistent disparities in air pollution exposure and associated health impacts. Advances in air quality measurement, models, and analytic methods have demonstrated the importance of finer-scale data and analysis in accurately quantifying the extent of inequity in intraurban pollution exposure, although the necessary degree of spatial resolution remains a complex and context-dependent question.

OBJECTIVE

The objectives of this commentary were to a) discuss ways to maximize and evaluate the effectiveness of efforts to reduce air pollution disparities, and b) argue that environmental regulators must employ improved methods to project, measure, and track the distributional impacts of new policies at finer geographic and temporal scales.

DISCUSSION

The historic federal investments from the Inflation Reduction Act, the Infrastructure Investment and Jobs Act, and the Biden Administration's commitment to Justice40 present an unprecedented opportunity to advance climate and energy policies that deliver real reductions in pollution-related health inequities. In our opinion, scientists, advocates, policymakers, and implementing agencies must work together to harness critical advances in air quality measurements, models, and analytic methods to ensure success. https://doi.org/10.1289/EHP13063.

Race- and Gender-Specific Associations between Neighborhood-Level Socioeconomic Status and Body Mass Index: Evidence from the Southern Community Cohort Study

Obesity and a low socioeconomic status (SES), measured at the neighborhood level, are more common among Americans of Black race and with a low individual-level SES. We examined the association between the neighborhood SES and body mass index (BMI) using data from 80,970 participants in the Southern Community Cohort Study, a cohort that oversamples Black and low-SES participants. BMI (kg/m2) was examined both continuously and categorically using cut points defined by the CDC. Neighborhood SES was measured using a neighborhood deprivation index composed of census-tract variables in the domains of education, employment, occupation, housing, and poverty. Generally, the participants in lower-SES neighborhoods were more likely to have a higher BMI and to be considered obese. We found effect modification by race and sex, where the neighborhood-BMI association was most apparent in White female participants in all the quintiles of the neighborhood SES (ORQ2 = 1.55, 95%CI = 1.34, 1.78; ORQ3 = 1.71, 95%CI = 1.48, 1.98; ORQ4 = 1.76, 95%CI = 1.52, 2.03; ORQ5 = 1.64, 95%SE = 1.39, 1.93). Conversely, the neighborhood-BMI association was mostly null in Black male participants (ORQ2 = 0.91, 95%CI = 0.72, 1.15; ORQ3 = 1.05, 95%CI = 0.84, 1.31; βQ4 = 1.00, 95%CI = 0.81, 1.23; ORQ5 = 0.76, 95%CI = 0.63, 0.93). Within all the subgroups, the associations were attenuated or null in participants residing in the lowest-SES neighborhoods. These findings suggest that the associations between the neighborhood SES and BMI vary, and that other factors aside from the neighborhood SES may better predict the BMI in Black and low-SES groups.

Census Tracts Are Not Neighborhoods: Addressing Spatial Misalignment in Studies Examining the Impact of Historical Redlining on Present-day Health Outcomes

BACKGROUND

Research examining the effects of historical redlining on present-day health outcomes is often complicated by the misalignment of contemporary census boundaries with the neighborhood boundaries drawn by the US Home Owners' Loan Corporation (HOLC) in the 1930s. Previous studies have used different approaches to assign historical HOLC grades to contemporary geographies, but how well they capture redlining exposure is unknown.

METHODS

Our analysis included 7711 residences identified in the Multiple Listing Service database in Atlanta, Georgia (2017-2022). We evaluated the classification of HOLC grade assignment (A, B, C, D, or ungraded) when assigning exposure under four area-level approaches (centroid, majority land area, weighted score, and highest HOLC) compared with using complete address data (gold standard). We additionally compared approaches across three 2020 census geographies (tract, block group, and block).

RESULTS

When comparing the use of census tracts to complete address data, sensitivity was highest for the weighted score approach, which correctly identified 77% of residences in truly A-D graded neighborhoods as compared with the majority land area (44%), centroid (54%), and highest HOLC (59%) approaches. Regarding specificity, the majority land area approach best-classified residences in truly ungraded neighborhoods (93%) as compared with the weighted score (65%), centroid (81%), and highest HOLC (54%) approaches. Classification improved regardless of approach when using census block compared with the census tract.

CONCLUSIONS

Misclassification of historical redlining exposure is inevitable when using contemporary census geographies rather than complete address data. This study provides a framework for assessing spatial misalignment and selecting an approach for classification.

Examining the geographical distribution of air pollution disparities across different racial and ethnic groups: Incorporating workplace addresses

BACKGROUND

Most previous studies on air pollution exposure disparities among racial and ethnic groups in the US have been limited to residence-based exposure and have given little consideration to population mobility and spatial patterns of residences, workplaces, and air pollution. This study aimed to examine air pollution exposure disparities by racial and ethnic groups while explicitly accounting for both the work-related activity of the population and localized spatial patterns of residential segregation, clustering of workplaces, and variability of air pollutant concentration.

METHOD

In the present study, we assessed population-level exposure to air pollution using tabulated residence and workplace addresses of formally employed workers from LEHD Origin-Destination Employment Statistics (LODES) data at the census tract level across eight Metropolitan Statistical Areas (MSAs). Combined with annual-averaged predictions for three air pollutants (PM2.5, NO2, O3), we investigated racial and ethnic disparities in air pollution exposures at home and workplaces using pooled (i.e., across eight MSAs) and regional (i.e., with each MSA) data.

RESULTS

We found that non-White groups consistently had the highest levels of exposure to all three air pollutants, at both their residential and workplace locations. Narrower exposure disparities were found at workplaces than residences across all three air pollutants in the pooled estimates, due to substantially lower workplace segregation than residential segregation. We also observed that racial disparities in air pollution exposure and the effect of considering work-related activity in the exposure assessment varied by region, due to both the levels and patterns of segregation in the environments where people spend their time and the local heterogeneity of air pollutants.

CONCLUSIONS

The results indicated that accounting for workplace activity illuminates important variation between home- and workplace-based air pollution exposure among racial and ethnic groups, especially in the case of NO2. Our findings suggest that consideration of both activity patterns and place-based exposure is important to improve our understanding of population-level air pollution exposure disparities, and consequently to health disparities that are closely linked to air pollution exposure.