Racial isolation and exposure to airborne particulate matter and ozone in understudied US populations: Environmental justice applications of downscaled numerical model output

Racial/ethnic disparities in tuberculosis incidence linked to PM2.5 constituents and their sources in the United States, 2000 - 2019: a population-based study

BACKGROUND

Racial/ethnic disparities in the effects of PM2.5 constituents and their sources on tuberculosis (TB) incidence remain unclear.

METHODS

We collected data on TB incidence in 49 states of the United States (US) during 2000 - 2019. Two-way fixed effects models were employed to assess the effects of 15 PM2.5 constituents, and the non-negative matrix factorization analysis was additionally performed to explore the effects of sources of PM2.5 constituents. The generalized weighted quantile sum method was applied to determine the relative contribution of each PM2.5 constituent. Racial/ethnic disparities were evaluated in the form of absolute and relative disparities.

RESULTS

Effects of most PM2.5 constituents on TB incidence in the Hispanic people were stronger than those in others, with an interquartile range increase in constituents associated with 1.25 (95% CI: 0.48 to 2.02 for potassium) to 4.10 (95% CI: 3.27 to 4.94 for sulfate) additional TB cases per 100,000 individuals annually in the Hispanic people. The absolute disparity in PM2.5-attributable TB burden between the Hispanic and White people decreased from 11.07 to 6.48 cases per 100,000 individuals, while the relative disparity enlarged from 15.75 in 2000 to 16.17 in 2019. Sulfate was the most influential constituent to TB incidence for the White (32.0%), Hispanic people (26.1%), and people of other races/ethnicities (17.9%). PM2.5 from oil combustion/motor vehicle traffic increased TB incidence in the Hispanic people and people of other races/ethnicities. TB incidence was positively associated with PM2.5 from biomass and coal burning across most of races/ethnicities.

CONCLUSIONS

More efforts targeted at the Hispanic people are needed to narrow the PM2.5-attributable racial/ethnic health inequities in TB. Reducing PM2.5 from oil combustion/motor vehicle traffic, biomass and coal burning would contribute to TB elimination in the US.

Air pollution exposure disparities among ethnic groups in high-income countries: A scoping review

BACKGROUND

The adverse health effects of air pollution are well-established. Previous reviews have highlighted disparities in air pollution exposure between minoritized ethnic groups and majoritized ethnic groups. However, these reviews primarily focused on proximity to pollution sources rather than objectively measured concentrations. This scoping review aims to provide an overview of the extent of inequalities in objectively measured air pollution exposure among ethnic groups in high-income countries.

METHODS

We systematically searched PubMed, Scopus, Web of Science, and Google Scholar for studies published in English, that reported on objectively measured air pollution exposure stratified by ethnic groups in high-income countries. Data on study characteristics and air pollution exposure were extracted.

RESULTS

The majority of all 55 included studies were conducted in North America (n = 46), followed by Europe (n = 8), and Oceania (n = 1). Across studies, 25 ethnic groups were identified, with African American, Hispanic, Latino, and Asian populations being the most studied minoritized ethnic groups. PM2.5 was the most studied (n = 38) air pollutant. Eighteen studies statistically tested differences in exposure across ethnic groups. Thirteen studies reported significantly higher air pollution exposure among minoritized ethnic populations compared to the majoritized ethnic population, and five studies showed mixed evidence.

CONCLUSIONS

This review highlights the extent of disparities in air pollution exposure among ethnic groups in high-income countries. It underscores the need for further research to understand the contributing factors and potential interventions to address these disparities.

Southern California ozone exposure disparities under different emissions control strategies in a low-carbon future

Environmental justice (EJ) has emerged as a critical consideration when planning new air pollution control strategies. In this study we analyze how traditional ozone (O3) control strategies for the year 2050 will affect exposure disparities, defined as departures from the population average exposure, for O3 and oxides of nitrogen (NOx) in Southern California. Future air quality fields were simulated using a chemical transport model under five emission scenarios that explore a range of traditional controls that target the largest sources of precursor emissions using a novel O3 source apportionment technique but without considering exposure disparities. We find that traditional O3 control strategies reduce O3 exposure disparities by <1.6 % and reduce NO2 exposure disparities by <9 % in Southern California. For the Black and African residents living in the urban core of Los Angeles, the relative NO2 exposure disparities increase from +23.1 % to +66.2 % and O3 exposure disparities increase from -3.3 % to +0.1 % due to NOx emissions reductions mainly in outlying regions and the NOx-rich environment in the urban core. Additional analysis shows that complete elimination of NOx emissions from Los Angeles International Airport (LAX) would reduce the NO2 exposure disparities by up to 50 %, but there is currently no practical method to achieve this goal. The results of the current study highlight the challenge of simultaneously attaining O3 standards and reducing exposure disparities for O3 and NO2 in cities with NOx-rich urban cores. Reducing emissions by region may be a solution to this challenge.

The Interaction of Racial-Ethnic and Economic Concentration and its Association with Premature Mortality in U.S. Neighborhoods

Recent research shows a significant link between race-ethnicity and income concentration and premature death rates in the U.S. However, most studies focus on Black-White residential concentration, overlooking racial-ethnic diversity. Our study examines the impact of racial-ethnic majority composition on mortality and how this relationship varies across different levels of economic concentration in neighborhoods, as defined by census tracts. Premature death rates (under 65 years of age) were retrieved from abridged period life tables from 67,140 U.S. census tracts derived from the U.S. Small-area Life Expectancy Project. Covariate factors were retrieved from the 2011-2015 American Community Survey (ACS) 5-year estimates. We measured racial-ethnic concentration by grouping neighborhoods using each tract's majority racial-ethnic group, and approximated income concentration using the Index of Concentration of the Extremes. We used three-level random intercept models to examine the interaction of racial-ethnic and income concentration and its association with neighborhood mortality risk, accounting for covariates. Our study yielded three salient findings. First, mortality risk varied greatly in poor neighborhoods with different racial-ethnic compositions compared to affluent neighborhoods, with notable higher risk in Black-majority areas. Second, in diverse neighborhoods where no single ethnic group forms a majority-referred to as Minority-majority neighborhoods-the mortality risk is comparable to that in White-majority neighborhoods. Third, Hispanic/Latino- and Asian-majority neighborhoods had lower mortality risk than White-majority neighborhoods in areas with a high concentration of poverty, but similar mortality risk in affluent areas. The study suggests that racial-ethnic and socioeconomic area-based measures are important to consider together to address mortality inequities accurately.

Neighborhood Racial and Ethnic Segregation and the Risk of Dementia in Older Adults Living with Kidney Failure

Key Points

Background

Dementia disproportionately affects older minoritized adults with kidney failure. To better understand the mechanism of this disparity, we studied the role of racial and ethnic segregation (segregation hereafter), i.e., a form of structural racism recently identified as a mechanism in numerous other health disparities.

Methods

We identified 901,065 older adults (aged ≥55 years) with kidney failure from 2003 to 2019 using the United States Renal Data System. We quantified dementia risk across tertiles of residential neighborhood segregation score using cause-specific hazard models, adjusting for individual- and neighborhood-level factors. We included an interaction term to quantify the differential effect of segregation on dementia diagnosis by race and ethnicity.

Results

We identified 79,851 older adults with kidney failure diagnosed with dementia between 2003 and 2019 (median follow-up: 2.2 years). Compared with those in low-segregation neighborhoods, older adults with kidney failure in high-segregation neighborhoods had a 1.63-fold (95% confidence interval [CI], 1.60 to 1.66) higher risk of dementia diagnosis, an association that differed by race and ethnicity (Asian: adjusted hazard ratio [aHR] = 1.26, 95% CI, 1.15 to 1.38; Black: aHR = 1.66, 95% CI, 1.61 to 1.71; Hispanic: aHR = 2.05, 95% CI, 1.93 to 2.18; White: aHR = 1.59, 95% CI, 1.55 to 1.64; P interaction < 0.001). Notably, older Asian (aHR = 1.76; 95% CI, 1.64 to 1.89), Black (aHR = 2.65; 95% CI, 2.54 to 2.77), Hispanic (aHR = 2.15; 95% CI, 2.04 to 2.26), and White (aHR = 2.20; 95% CI, 2.09 to 2.31) adults with kidney failure residing in minority-predominant high-segregation neighborhoods had a higher risk of dementia diagnosis compared with older White adults with kidney failure in White-predominant high-segregation neighborhoods. Moreover, older adults with kidney failure receiving care at dialysis facilities located in high-segregation neighborhoods also experienced a higher risk of dementia diagnosis (aHR = 1.53; 95% CI, 1.50 to 1.56); this association differed by race and ethnicity (P interaction < 0.001).

Conclusions

Residing in or receiving care at dialysis facilities located in high-segregation neighborhoods was associated with a higher risk of dementia diagnosis among older individuals with kidney failure, particularly minoritized individuals.

The role of cultural competency training to address health disparities in surgical settings

BACKGROUND

Disparities in health care delivered to marginalized groups are unjust and result in poor health outcomes that increase the cost of care for everyone. These disparities are largely avoidable and health care providers, have been targeted with education and specialised training to address these disparities.

SOURCES OF DATA

In this manuscript we have sought out both peer-reviewed material on Pubmed, as well as policy statements on the potential role of cultural competency training (CCT) for providers in the surgical care setting. The goal of undertaking this work was to determine whether there is evidence that these endeavours are effective at reducing disparities.

AREAS OF AGREEMENT

The unjustness of health care disparities is universally accepted.

AREAS OF CONTROVERSY

Whether the outcome of CCT justifies the cost has not been effectively answered.

GROWING POINTS

These include the structure/content of the CCT and whether the training should be delivered to teams in the surgical setting.

AREAS TIMELY FOR DEVELOPING RESEARCH

Because health outcomes are affected by many different inputs, should the effectiveness of CCT be improvement in health outcomes or should we use a proxy or a surrogate of health outcomes.

Prenatal Cannabis Use and Offspring Autism-Related Behaviors: Examining Maternal Stress as a Moderator in a Black American Cohort

Prenatal cannabis use and maternal stress have been proposed as risk factors for autism spectrum disorder (ASD). Black mothers and mothers of lower socioeconomic status (SES) may be especially likely to experience high levels of stress. This study examined the impact of prenatal cannabis use and maternal stress (i.e., prenatal distress, racial discrimination, and lower SES) on child ASD-related behaviors in a sample of 172 Black mother-child pairs. We found that prenatal stress was significantly associated with ASD-related behaviors. Prenatal cannabis use did not predict ASD-related behaviors and did not interact with maternal stress to predict ASD-related behaviors. These findings replicate previous work on prenatal stress-ASD associations and add to the limited literature on prenatal cannabis-ASD associations in Black samples.

Sociodemographic inequities in the burden of carcinogenic industrial air emissions in the United States

BACKGROUND

Industrial facilities are not located uniformly across communities in the United States, but how the burden of exposure to carcinogenic air emissions may vary across population characteristics is unclear. We evaluated differences in carcinogenic industrial pollution among major sociodemographic groups in the United States and Puerto Rico.

METHODS

We evaluated cross-sectional associations of population characteristics including race and ethnicity, educational attainment, and poverty at the census tract level with point-source industrial emissions of 21 known human carcinogens using regulatory data from the US Environmental Protection Agency. Odds ratios and 95% confidence intervals comparing the highest emissions (tertile or quintile) to the referent group (zero emissions [ie, nonexposed]) for all sociodemographic characteristics were estimated using multinomial, population density-adjusted logistic regression models.

RESULTS

In 2018, approximately 7.4 million people lived in census tracts with nearly 12 million pounds of carcinogenic air releases. The odds of tracts having the greatest burden of benzene, 1,3-butadiene, ethylene oxide, formaldehyde, trichloroethylene, and nickel emissions compared with nonexposed were 10%-20% higher for African American populations, whereas White populations were up to 18% less likely to live in tracts with the highest emissions. Among Hispanic and Latino populations, odds were 16%-21% higher for benzene, 1,3-butadiene, and ethylene oxide. Populations experiencing poverty or with less than high school education were associated with up to 51% higher burden, irrespective of race and ethnicity.

CONCLUSIONS

Carcinogenic industrial emissions disproportionately impact African American and Hispanic and Latino populations and people with limited education or experiencing poverty thus representing a source of pollution that may contribute to observed cancer disparities.

Assessment of census-tract level socioeconomic position as a modifier of the relationship between short-term PM2.5 exposure and cardiovascular emergency department visits in Missouri

INTRODUCTION

Ambient particulate matter ≤ 2.5 µm in aerodynamic diameter (PM2.5) exposure elevates the risk for cardiovascular disease morbidity (CVDM). The aim of this study is to characterise which area-level measures of socioeconomic position (SEP) modify the relationship between PM2.5 exposure and CVDM in Missouri at the census-tract (CT) level.

METHODS

We use individual level Missouri emergency department (ED) admissions data (n=3 284 956), modelled PM2.5 data, and yearly CT data from 2012 to 2016 to conduct a two-stage analysis. Stage one uses a case-crossover approach with conditional logistic regression to establish the baseline risk of ED visits associated with IQR changes in PM2.5. In the second stage, we use multivariate metaregression to examine how CT-level SEP modifies the relationship between ambient PM2.5 exposure and CVDM.

RESULTS

We find that overall, ambient PM2.5 exposure is associated with increased risk for CVDM. We test effect modification in statewide and urban CTs, and in the warm season only. Effect modification results suggest that among SEP measures, poverty is most consistently associated with increased risk for CVDM. For example, across Missouri, the highest poverty CTs are at an elevated risk for CVDM (OR=1.010 (95% CI 1.007 to 1.014)) compared with the lowest poverty CTs (OR=1.004 (95% CI 1.000 to 1.008)). Other SEP modifiers generally display an inconsistent or null effect.

CONCLUSION

Overall, we find some evidence that area-level SEP modifies the relationship between ambient PM2.5 exposure and CVDM, and suggest that the relationship between air-pollution, area-level SEP and CVDM may be sensitive to spatial scale.

Neighborhood Segregation and Access to Live Donor Kidney Transplantation

Importance

Identifying the mechanisms of structural racism, such as racial and ethnic segregation, is a crucial first step in addressing the persistent disparities in access to live donor kidney transplantation (LDKT).

Objective

To assess whether segregation at the candidate's residential neighborhood and transplant center neighborhood is associated with access to LDKT.

Design, Setting, and Participants

In this cohort study spanning January 1995 to December 2021, participants included non-Hispanic Black or White adult candidates for first-time LDKT reported in the US national transplant registry. The median (IQR) follow-up time for each participant was 1.9 (0.6-3.0) years.

Main Outcome and Measures

Segregation, measured using the Theil H method to calculate segregation tertiles in zip code tabulation areas based on the American Community Survey 5-year estimates, reflects the heterogeneity in neighborhood racial and ethnic composition. To quantify the likelihood of LDKT by neighborhood segregation, cause-specific hazard models were adjusted for individual-level and neighborhood-level factors and included an interaction between segregation tertiles and race.

Results

Among 162 587 candidates for kidney transplant, the mean (SD) age was 51.6 (13.2) years, 65 141 (40.1%) were female, 80 023 (49.2%) were Black, and 82 564 (50.8%) were White. Among Black candidates, living in a high-segregation neighborhood was associated with 10% (adjusted hazard ratio [AHR], 0.90 [95% CI, 0.84-0.97]) lower access to LDKT relative to residence in low-segregation neighborhoods; no such association was observed among White candidates (P for interaction = .01). Both Black candidates (AHR, 0.94 [95% CI, 0.89-1.00]) and White candidates (AHR, 0.92 [95% CI, 0.88-0.97]) listed at transplant centers in high-segregation neighborhoods had lower access to LDKT relative to their counterparts listed at centers in low-segregation neighborhoods (P for interaction = .64). Within high-segregation transplant center neighborhoods, candidates listed at predominantly minority neighborhoods had 17% lower access to LDKT relative to candidates listed at predominantly White neighborhoods (AHR, 0.83 [95% CI, 0.75-0.92]). Black candidates residing in or listed at transplant centers in predominantly minority neighborhoods had significantly lower likelihood of LDKT relative to White candidates residing in or listed at transplant centers located in predominantly White neighborhoods (65% and 64%, respectively).

Conclusions

Segregated residential and transplant center neighborhoods likely serve as a mechanism of structural racism, contributing to persistent racial disparities in access to LDKT. To promote equitable access, studies should assess targeted interventions (eg, community outreach clinics) to improve support for potential candidates and donors and ultimately mitigate the effects of segregation.

Formaldehyde Exposure Racial Disparities in Southeast Texas

Formaldehyde (HCHO) exposures during a full year were calculated for different race/ethnicity groups living in Southeast Texas using a chemical transport model tagged to track nine emission categories. Petroleum and industrial emissions were the largest anthropogenic sources of HCHO exposure in Southeast Texas, accounting for 44% of the total HCHO population exposure. Approximately 50% of the HCHO exposures associated with petroleum and industrial sources were directly emitted (primary), while the other 50% formed in the atmosphere (secondary) from precursor emissions of reactive compounds such as ethylene and propylene. Biogenic emissions also formed secondary HCHO that accounted for 11% of the total population-weighted exposure across the study domain. Off-road equipment contributed 3.7% to total population-weighted exposure in Houston, while natural gas combustion contributed 5% in Beaumont. Mobile sources accounted for 3.7% of the total HCHO population exposure, with less than 10% secondary contribution. Exposure disparity patterns changed with the location. Hispanic and Latino residents were exposed to HCHO concentrations +1.75% above average in Houston due to petroleum and industrial sources and natural gas sources. Black and African American residents in Beaumont were exposed to HCHO concentrations +7% above average due to petroleum and industrial sources, off-road equipment, and food cooking. Asian residents in Beaumont were exposed to HCHO concentrations that were +2.5% above average due to HCHO associated with petroleum and industrial sources, off-road vehicles, and food cooking. White residents were exposed to below average HCHO concentrations in all domains because their homes were located further from primary HCHO emission sources. Given the unique features of the exposure disparities in each region, tailored solutions should be developed by local stakeholders. Potential options to consider in the development of those solutions include modifying processes to reduce emissions, installing control equipment to capture emissions, or increasing the distance between industrial sources and residential neighborhoods.

Is residential exposure to oil refineries a novel contextual risk factor for coronary heart disease?

Despite a multi-decade decrease in cardiovascular disease, geographic disparities have widened, with excess mortality concentrated within the United States (U.S.) South. Petroleum production and refining, a major contributor to climate change, is concentrated within the U.S. South and emits multiple classes of atherogenic pollutants. We investigated whether residential exposure to oil refineries could explain variation in self-reported coronary heart disease (CHD) prevalence among adults in southern states for the year 2018, where the majority of oil refinery activity occurs (Alabama, Mississippi, Louisiana, Arkansas, Texas, New Mexico, and Oklahoma). We examined census tract-level association between oil refineries and CHD prevalence. We used a double matching method to adjust for measured and unmeasured spatial confounders: one-to-n distance matching and one-to-one generalized propensity score matching. Exposure metrics were constructed based on proximity to refineries, activities of refineries, and wind speed/direction. For all census tracts within 10 km of refineries, self-reported CHD prevalence ranged from 1.2% to 17.6%. Compared to census tracts located at ≥5 km and <10 km, one standard deviation increase in the exposure within 5 km of refineries was associated with a 0.33 (95% confidence interval: 0.04, 0.63) percentage point increase in the prevalence. A total of 1119.0 (123.5, 2114.2) prevalent cases or 1.6% (0.2, 3.1) of CHD prevalence in areas within 5 km from refineries were potentially explained by exposure to oil refineries. At the census tract-level, the prevalence of CHD explained by exposure to oil refineries ranged from 0.02% (0.00, 0.05) to 47.4% (5.2, 89.5). Thus, although we cannot rule out potential confounding by other personal risk factors, CHD prevalence was found to be higher in populations living nearer to oil refineries, which may suggest that exposure to oil refineries can increase CHD risk, warranting further investigation.

Ambient air pollution is associated with graft failure/death in pediatric liver transplant recipients

Children exposed to disproportionately higher levels of air pollution experience worse health outcomes. In this population-based, observational registry study, we examine the association between air pollution and graft failure/death in children following liver transplantation (LT) in the US. We modeled the associations between air pollution (PM2.5) levels localized to the patient's ZIP code at the time of transplant and graft failure or death using Cox proportional-hazards models in pediatric LT recipients aged <19 years in the US from 2005-2015. In univariable analysis, high neighborhood PM2.5 was associated with a 56% increased hazard of graft failure/death (HR: 1.56; 95% CI: 1.32, 1.83; P < .001). In multivariable analysis, high neighborhood PM2.5 was associated with a 54% increased risk of graft failure/death (HR: 1.54; 95% CI: 1.29, 1.83; P < .001) after adjusting for race as a proxy for racism, insurance status, rurality, and neighborhood socioeconomic deprivation. Children living in high air pollution neighborhoods have an increased risk of graft failure and death posttransplant, even after controlling for sociodemographic variables. Our findings add further evidence that air pollution contributes to adverse health outcomes for children posttransplant and lay the groundwork for future studies to evaluate underlying mechanisms linking PM2.5 to adverse LT outcomes.

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.

Climate change and cancer: the Environmental Justice perspective

Despite advances in cancer control-prevention, screening, diagnosis, treatment, and survivorship-racial disparities in cancer incidence and survival persist and, in some cases, are widening in the United States. Since 2020, there's been growing recognition of the role of structural racism, including structurally racist policies and practices, as the main factor contributing to historical and contemporary disparities. Structurally racist policies and practices have been present since the genesis of the United States and are also at the root of environmental injustices, which result in disproportionately high exposure to environmental hazards among communities targeted for marginalization, increased cancer risk, disruptions in access to care, and worsening health outcomes. In addition to widening cancer disparities, environmental injustices enable the development of polluting infrastructure, which contribute to detrimental health outcomes in the entire population, and to climate change, the most pressing public health challenge of our time. In this commentary, we describe the connections between climate change and cancer through an Environmental Justice perspective (defined as the fair treatment and meaningful involvement of people of all racialized groups, nationalities, or income, in all aspects, including development, implementation, and enforcement, of policies and practices that affect the environment and public health), highlighting how the expertise developed in communities targeted for marginalization is crucial for addressing health disparities, tackling climate change, and advancing cancer control efforts for the entire population.

A cross-sectional study of inequalities in digital air pollution information access and exposure reducing behavior uptake in the UK

Air pollution is a pervasive global environmental challenge that presents substantial and differential risk across populations. Individual-level pollution exposure is a function of varying factors, including but not limited to geographic location, proximity to point sources, ventilation, and behavioral patterns. Mounting evidence suggests that informational interventions can play a substantial role in mediating exposures for specific population subgroups and reduce downstream adverse health outcomes. The literature has yet to address whether access to air quality information is sociodemographically stratified, and whether such access correlates with increased uptake of exposure reducing behaviors at the population level. This study represents a first step in answering these questions by analysing responses from the "Clean Air Public Insight Tracker" nationally representative survey (n = 1,993) of the UK population, administered by UK charity Global Action Plan. Results from logistic regression and zero-inflated negative binomial models estimate 28% of the population have accessed air pollution information, while the odds of younger individuals (ages 18-36), men, and non-white individuals of accessing digitally available air quality information are greater that those outside these categories. Additionally, the odds of behavior uptake is greater if an individual accesses digital information sources like the internet, mobile apps or social media, has a higher education qualification or cares for someone with a health condition. These findings contribute to the growing literature surrounding which population groups engage with environmental and health-relevant information channels, and what connects engagement with air quality channels and uptake of exposure reducing behaviors. These results reinforce the need for additional research around air pollution informational alerts and exploring causal links between specific exposure reducing behaviours and improved health outcomes. It can also help inform the flow of resources and targeting of informational campaigns towards sociodemographic groups that are less likely to engage with air quality information.

Neighborhood Disadvantage, Race and Ethnicity, and Postpartum Depression

Importance

Postpartum depression (PPD) is a debilitating condition with higher rates among Black individuals. Increasingly, neighborhood disadvantage is being recognized as a contributor to poor health and may be associated with adverse postpartum mental health; however, associations between neighborhood disadvantage, race and ethnicity, and PPD have not been examined.

Objective

To investigate the association between neighborhood disadvantage and PPD and evaluate the extent to which these associations may differ by race and ethnicity.

Design, Setting, and Participants

This population-based cross-sectional study included 122 995 postpartum Kaiser Permanente Northern California members 15 years or older with a live birth between October 7, 2012, and May 31, 2017, and an address in the electronic health record. Analyses were conducted from June 1, 2022, through June 30, 2023.

Exposures

Neighborhood disadvantage defined using quartiles of the Neighborhood Deprivation Index (NDI), a validated census-based socioeconomic status measure; self-reported race and ethnicity ascertained from Kaiser Permanente Northern California electronic health records.

Main Outcomes and Measures

Multivariable Poisson regression was conducted to assess associations between neighborhood disadvantage, race and ethnicity, and a diagnosis of PPD.

Results

Of 122 995 included postpartum individuals, 17 554 (14.3%) were younger than 25 years, 29 933 (24.3%) were Asian, 8125 (6.6%) were Black, 31 968 (26.0%) were Hispanic, 47 527 (38.6%) were White, 5442 (4.4%) were of other race and ethnicity, and 15 436 (12.6%) had PPD. Higher neighborhood disadvantage and race and ethnicity were associated with PPD after covariate adjustment. Compared with White individuals, Black individuals were more likely to have PPD (adjusted relative risk [ARR], 1.30; 95% CI, 1.24-1.37), whereas Asian (ARR, 0.48; 95% CI, 0.46-0.50), and Hispanic (ARR, 0.92; 95% CI, 0.89-0.96) individuals and those identified as having other race and ethnicity (ARR, 95% CI, 0.90; 0.85-0.98) were less likely to have PPD. Associations between NDI and PPD differed by race and ethnicity (likelihood ratio test for interaction, χ212 = 41.36; P < .001). Among Black individuals, the risk of PPD was the greatest overall and increased with neighborhood disadvantage in a dose-response manner (quartile [Q] 2 ARR, 1.39 [95% CI, 1.13-1.71]; Q3 ARR, 1.50 [95% CI, 1.23-1.83]; Q4 ARR, 1.60 [95% CI, 1.32-1.93]; Cochrane-Armitage test for trend, P < .001). Neighborhood disadvantage was associated with PPD among Asian (Q2 ARR, 1.17 [95% CI, 1.04-1.31]; Q3 ARR, 1.20 [95% CI, 1.06-1.35]) and White (Q3 ARR, 1.14 [95% CI, 1.07-1.21]; Q4 ARR, 1.17 [95% CI, 1.09-1.26]) individuals and those of other race and ethnicity (Q3 ARR, 1.34 [95% CI, 1.09-1.63]; Q4 ARR, 1.28 [95% CI, 1.03-1.58]), but the magnitude of risk was lower. Neighborhood disadvantage was not associated with PPD among Hispanic individuals (eg, Q2 ARR, 1.04 [95% CI, 0.94-1.14]; Q3 ARR, 1.00 [95% CI, 0.91-1.10]; Q4 ARR, 0.98 [95% CI, 0.90-1.08]).

Conclusions and Relevance

In this cross-sectional study of postpartum individuals, residing in more disadvantaged neighborhoods was associated with PPD, except among Hispanic individuals. Neighborhood disadvantage may be associated with racial and ethnic differences in postpartum mental health. Geographic targeting of mental health interventions may decrease postpartum mental health inequities.

Uncertainty Reduction and Environmental Justice in Air Pollution Epidemiology: The Importance of Minority Representation

Ambient air pollution is an increasing threat to society, with rising numbers of adverse outcomes and exposure inequalities worldwide. Reducing uncertainty in health outcomes models and exposure disparity studies is therefore essential to develop policies effective in protecting the most affected places and populations. This study uses the concept of information entropy to study tradeoffs in mortality uncertainty reduction from increasing input data of air pollution versus health outcomes. We study a case scenario for short-term mortality from particulate matter (PM2.5) in North Carolina for 2001-2016, employing a case-crossover design with inputs from an individual-level mortality data set and high-resolution gridded data sets of PM2.5 and weather covariates. We find a significant association between mortality and PM2.5, and the information tradeoffs indicate that a 10% increase in mortality information reduces model uncertainty three times more than increased resolution of the air pollution model from 12 to 1 km. We also find that Non-Hispanic Black (NHB) residents tend to live in relatively more polluted census tracts, and that the mean PM2.5 for NHB cases in the mortality model is significantly higher than that of Non-Hispanic White cases. The distinct distribution of PM2.5 for NHB cases results in a relatively higher information value, and therefore faster uncertainty reduction, for new NHB cases introduced into the mortality model. This newfound influence of exposure disparities in the rate of uncertainty reduction highlights the importance of minority representation in environmental research as a quantitative advantage to produce more confident estimates of the true effects of environmental pollution.

Association between Low Urban Neighborhood Greenness and Hypertensive Disorders of Pregnancy

OBJECTIVE

Urban neighborhood greenness is associated with greater cardiovascular health in the general population, and with better pregnancy and neonatal outcomes. Hypertension in pregnancy is a leading cause of maternal mortality and long-term cardiovascular morbidity and mortality in women. We sought to examine the association between greenness and hypertensive disorders of pregnancy.

STUDY DESIGN

This study is a secondary analysis of a prospective cohort study of 1,943 women who received prenatal care from December 2013 to December 2016 at a single, urban, and tertiary academic medical center in Philadelphia, PA. Greenness measure was quantified via residential tree canopy cover within circumferential buffers of 100- and 500-meter radii around participants' homes. Associations between greenness and hypertensive disorders of pregnancy (defined as gestational hypertension or preeclampsia) were estimated by using multilevel logistic regression accounting for maternal sociodemographic information (race-ethnicity, insurance status, and age) medical history (diabetes, body mass index, smoking history, and parity), neighborhood deprivation index, and including 1,225 Philadelphia residents for whom key exposure and outcome data were available.

RESULTS

At baseline, the participants' mean (SD) age was 27.5 (5.9) years, (range: 14-44 years). The majority of participants were non-Hispanic Black (857, 70.2%). Participants with less residential tree canopy cover were significantly more likely to have hypertensive disorders of pregnancy. The multivariable-adjusted odds ratio of hypertensive disorders of pregnancy among participants with less than 10% compared with those with greater than 30% tree canopy cover was 2.14 (95% confidence interval [CI]: 1.11-4.15) within 100-meter buffer.

CONCLUSION

In our cohort, greenness was associated with lower hypertensive disorders of pregnancy odds. Our findings add to evidence that greenness may confer health benefits and warrant further investigations in identifying whether there is a causal pathway through which greenness may be protective against hypertensive disorders of pregnancy.

KEY POINTS

· Low residential tree canopy is associated with increased risk of hypertensive disorders of pregnancy. · 100-meter buffers are most sensitive in identifying associations between tree canopy and HDP risk. · The role of greenness against hypertensive disorders of pregnancy should be further studied experimentally.

Long-term air pollution exposure and markers of cardiometabolic health in the National Longitudinal Study of Adolescent to Adult Health (Add Health)

BACKGROUND

Air pollution exposure is associated with cardiovascular morbidity and mortality. Although exposure to air pollution early in life may represent a critical window for development of cardiovascular disease risk factors, few studies have examined associations of long-term air pollution exposure with markers of cardiovascular and metabolic health in young adults.

OBJECTIVES

By combining health data from the National Longitudinal Study of Adolescent to Adult Health (Add Health) with air pollution data from the Fused Air Quality Surface using Downscaling (FAQSD) archive, we: (1) calculated multi-year estimates of exposure to ozone (O3) and particulate matter with an aerodynamic diameter ≤ 2.5 µm (PM2.5) for Add Health participants; and (2) estimated associations between air pollution exposures and multiple markers of cardiometabolic health.

METHODS

Add Health is a nationally representative longitudinal cohort study of over 20,000 adolescents aged 12-19 in the United States (US) in 1994-95 (Wave I). Participants have been followed through adolescence and into adulthood with five in-home interviews. Estimated daily concentrations of O3 and PM2.5 at census tracts were obtained from the FAQSD archive and used to generate tract-level annual averages of O3 and PM2.5 concentrations. We estimated associations between average O3 and PM2.5 exposures from 2002 to 2007 and markers of cardiometabolic health measured at Wave IV (2008-09), including hypertension, hyperlipidemia, body mass index (BMI), diabetes, C-reactive protein, and metabolic syndrome.

RESULTS

The final sample size was 11,259 individual participants. The average age of participants at Wave IV was 28.4 years (range: 24-34 years). In models adjusting for age, race/ethnicity, and sex, long-term O3 exposure (2002-07) was associated with elevated odds of hypertension, with an odds ratio (OR) of 1.015 (95% confidence interval [CI]: 1.011, 1.029); obesity (1.022 [1.004, 1.040]); diabetes (1.032 [1.009,1.054]); and metabolic syndrome (1.028 [1.014, 1.041]); PM2.5 exposure (2002-07) was associated with elevated odds of hypertension (1.022 [1.001, 1.045]).

CONCLUSION

Findings suggest that long-term ambient air pollution exposure, particularly O3 exposure, is associated with cardiometabolic health in early adulthood.

Latinx and Indigenous Mexican Caregivers' Perspectives of the Salton Sea Environment on Children's Asthma, Respiratory Health, and Co-Presenting Health Conditions

This research investigated Latinx and Indigenous Mexican caregivers' perspectives of the Salton Sea's environment (e.g., dust concentrations and other toxins) on child health conditions. The Salton Sea is a highly saline drying lakebed located in the Inland Southern California desert borderland region and is surrounded by agricultural fields. Children of Latinx and Indigenous Mexican immigrant families are especially vulnerable to the Salton Sea's environmental impact on chronic health conditions due to their proximity to the Salton Sea and structural vulnerability. From September 2020 to February 2021, we conducted semi-structured interviews and focus groups with a total of 36 Latinx and Indigenous Mexican caregivers of children with asthma or respiratory distress living along the Salton Sea. A community investigator trained in qualitative research conducted interviews in Spanish or Purépecha, an indigenous language spoken by immigrants from Michoacán, Mexico. Template and matrix analysis was used to identify themes and patterns across interviews and focus groups. Participants characterized the Salton Sea's environment as toxic, marked by exposure to sulfuric smells, dust storms, chemicals, and fires, all of which contribute to children's chronic health conditions (e.g., respiratory illnesses such as asthma, bronchitis, and pneumonia, co-presenting with allergies and nosebleeds). The findings have important environmental public health significance for structurally vulnerable child populations in the United States and globally.

Effect modification of the association between fine particulate air pollution during a wildfire event and respiratory health by area-level measures of socio-economic status, race/ethnicity, and smoking prevalence

Fine particulate air pollution (PM2.5) is decreasing in most areas of the United States, except for areas most affected by wildfires, where increasing trends in PM2.5 can be attributed to wildfire smoke. The frequency and duration of large wildfires and the length of the wildfire season have all increased in recent decades, partially due to climate change, and wildfire risk is projected to increase further in many regions including the western United States. Increasingly, empirical evidence suggests differential health effects from air pollution by class and race; however, few studies have investigated such differential health impacts from air pollution during a wildfire event. We investigated differential risk of respiratory health impacts during the 2008 northern California wildfires by a comprehensive list of socio-economic status (SES), race/ethnicity, and smoking prevalence variables. Regardless of SES level across nine measures of SES, we found significant associations between PM2.5 and asthma hospitalizations and emergency department (ED) visits during these wildfires. Differential respiratory health risk was found by SES for ED visits for chronic obstructive pulmonary disease where the highest risks were in ZIP codes with the lowest SES levels. Findings for differential effects by race/ethnicity were less consistent across health outcomes. We found that ZIP codes with higher prevalence of smokers had greater risk of ED visits for asthma and pneumonia. Our study suggests that public health efforts to decrease exposures to high levels of air pollution during wildfires should focus on lower SES communities.

Environmental characteristics and disparities in adult asthma in north central Texas urban counties

OBJECTIVES

Disparities in asthma prevalence present a persistent challenge to public health. The complex nature of the issue requires studies through a wide range of lenses. To date, little research has examined associations between asthma and multiple social and environmental factors simultaneously. This study aims to fill the gap with a focus on the impacts of multiple environmental characteristics and social determinants of health on asthma.

STUDY DESIGN

This study uses secondary analysis with data from a variety of sources to analyze the effects of environmental and social factors on adult asthma occurrence in North Central Texas.

METHOD

Hospital records and demographic and environmental data for four urban counties in North Central Texas (Collin, Dallas, Denton, and Tarrant) come from the Dallas/Fort Worth Hospital Council Foundation, the US census, the North Central Texas Council of Governments, and the Railroad Commission of Texas. The data were integrated using ArcGIS. A hotspot analysis was performed to inspect the spatial patterns of hospital visits for asthma exacerbations in 2014. The impacts of multiple environmental characteristics and social determinants of health were modeled using negative binomial regression.

RESULTS

The results revealed spatial clusters of adult asthma prevalence and disparities by race, class, and education. The occurrence of asthma exacerbations was positively associated with exposure to traffic-related air pollution, energy-related drilling activities, and older housing stock and negatively linked to green space.

CONCLUSIONS

Associations between built environmental characteristics and asthma prevalence have implications for urban planners, healthcare professionals, and policy makers. Empirical evidence for the role of social determinants of health supports continuing efforts in policies and practices to improve education and reduce socio-economic inequities.

Residential and Race/Ethnicity Disparities in Heat Vulnerability in the United States

Adverse health outcomes caused by extreme heat represent the most direct human health threat associated with the warming of the Earth's climate. Socioeconomic, demographic, health, land cover, and temperature determinants contribute to heat vulnerability; however, nationwide patterns of residential and race/ethnicity disparities in heat vulnerability in the United States are poorly understood. This study aimed to develop a Heat Vulnerability Index (HVI) for the United States; to assess differences in heat vulnerability across geographies that have experienced historical and/or contemporary forms of marginalization; and to quantify HVI by race/ethnicity. Principal component analysis was used to calculate census tract level HVI scores based on the 2019 population characteristics of the United States. Differences in HVI scores were analyzed across the Home Owners' Loan Corporation (HOLC) "redlining" grades, the Climate and Economic Justice Screening Tool (CEJST) disadvantaged versus non-disadvantaged communities, and race/ethnicity groups. HVI scores were calculated for 55,267 U.S. census tracts. Mean HVI scores were 17.56, 18.61, 19.45, and 19.93 for HOLC grades "A"-"D," respectively. CEJST-defined disadvantaged census tracts had a significantly higher mean HVI score (19.13) than non-disadvantaged tracts (16.68). The non-Hispanic African American or Black race/ethnicity group had the highest HVI score (18.51), followed by Hispanic or Latino (18.19). Historically redlined and contemporary CEJST disadvantaged census tracts and communities of color were found to be associated with increased vulnerability to heat. These findings can help promote equitable climate change adaptation policies by informing policymakers about the national distribution of place- and race/ethnicity-based disparities in heat vulnerability.

Communities of color are disproportionately exposed to long-term and short-term PM2.5 in metropolitan America

We conducted a novel investigation of neighborhood-level racial/ethnic exposure disparities employing measures aligned with long-term and short-term PM_2.5 air pollution benchmarks across metropolitan contexts of the contiguous United States, 2012-2016. We used multivariable generalized estimating equations (GEE) to quantify PM_2.5 exposure disparities based on the census tract composition of people of color (POC) and POC groups (Hispanic/Latina/x/o, Black, Asian). We examined eight census tract-level measures of longer-to-shorter term exposures derived from data on modeled daily ambient PM_2.5 concentrations. We found associations between increased POC composition and greater exposure to all PM_2.5 measures, with associations strengthening across measures of longer-to-shorter term exposures. In a GEE with a negative binomial distribution, a standard deviation increase in POC composition predicted a 0.6% increase (incidence rate ratio (IRR): 1.006, 95% confidence interval (CI): 1.005-1.008) in the number of days PM_2.5 concentrations were ≥5 μg/m³ (longest-term benchmark). In a GEE with an inverse Gaussian distribution, a standard deviation increase in POC composition predicted a 0.110 μg/m³ (1.0%) increase (B: 0.110, 95% CI: 0.076-0.143) in mean PM_2.5 concentration. In GEEs with a negative binomial distribution, the effect of a standard deviation increase in POC composition on exposure strengthened to 2.6% (IRR:1.026, 95% CI:1.017-1.035), 3.4% (IRR:1.034, 95% CI:1.022-1.047), 4.2% (IRR:1.042, 95% CI:1.025-1.058), 16.2% (IRR:1.162, 95% CI:1.117-1.210), 22.7% (IRR:1.227, 95% CI:1.137-1.325) and 28.3% (IRR:1.283, 95% CI:1.144-1.439) with respect to the number of days PM_2.5 concentrations were ≥10, 12, 15, 25, 35 and 55.5 μg/m³. POC group models indicated exposure disparities based on greater Hispanic/Latina/x/o, Asian, and Black composition. Evidence for stronger POC associations with shorter-term (higher concentration) PM_2.5 exceedances suggests that reducing PM_2.5 would attenuate racial/ethnic exposure disparities.

Unequal airborne exposure to toxic metals associated with race, ethnicity, and segregation in the USA

Persons of color have been exposed to a disproportionate burden of air pollution across the United States for decades. Yet, the inequality in exposure to known toxic elements of air pollution is unclear. Here, we find that populations living in racially segregated communities are exposed to a form of fine particulate matter with over three times higher mass proportions of known toxic and carcinogenic metals. While concentrations of total fine particulate matter are two times higher in racially segregated communities, concentrations of metals from anthropogenic sources are nearly ten times higher. Populations living in racially segregated communities have been disproportionately exposed to these environmental stressors throughout the past decade. We find evidence, however, that these disproportionate exposures may be abated though targeted regulatory action. For example, recent regulations on marine fuel oil not only reduced vanadium concentrations in coastal cities, but also sharply lessened differences in vanadium exposure by segregation.

Exploring environmenATL justice and data analytics in an environmental studies lab course

The environmental studies laboratory is an exciting place where students investigate, analyze, and reflect. Students test and apply theories and make abstract concepts concrete. As an example, ecology and environmental science are increasingly using "big data" to expand and refine research questions. This commentary reflects on the design and integration of an environmental justice and data analytics module in an environmental studies lab course. The module introduces an environmental justice framework to give students an understanding of tools and strategies to engage, assess, and intervene at multiple levels; while also developing advocacy and communication skills. Poor and minority populations have historically borne the brunt of environmental inequalities in the United States, suffering disproportionally from the effects of pollution, resource depletion, dangerous jobs, limited access to common resources, and exposure to environmental hazards. Paying particular attention to "redlining" and the ways that race, ethnicity, class, and gender have shaped the political and economic dimensions of environmental injustices, this module challenges students to critically examine redlining, socioeconomic, and environmental factors in Atlanta, Georgia (USA) to develop and explore research questions that may visually and/or statistically illuminate trends, patterns, and processes of environmenATL justice. This module also introduces some of the basic data handling and data analysis skills that give students an understanding of data types, descriptive statistics, sampling, and basic inferential statistics. By intentionally incorporating environmental justice activities and conversations in the classroom, instructors afford students an opportunity to engage in authentic examination of their world and make positive changes. Many of the skills learned and knowledge gained in this activity are directly transferable to post-baccalaureate studies (e.g., graduate school, medical school, professional training, etc.) and the world of employment. The module can also be adapted to various curriculum, courses, and communities.

Reductions in NO2 and emergency room visits associated with California's goods movement policies: A quasi-experimental study

INTRODUCTION

This study examines whether the "Emission Reduction Plan for Ports and Goods Movement" in California reduced air pollution exposures and emergency room visits among California Medicaid enrollees with asthma and/or chronic obstructive pulmonary disease.

METHOD

We created a retrospective cohort of 5608 Medicaid enrollees from ten counties in California with data from 2004 to 2010. We grouped the patients into two groups: those living within 500 m of goods movement corridors (ports and truck-permitted freeways), and control areas (away from the busy truck or car permitted highways). We created annual air pollution surfaces for nitrogen dioxide and assigned them to enrollees' home addresses. We used a quasi-experimental design with a difference-in-differences method to examine changes before and after the policy for cohort beneficiaries in the two groups.

RESULTS

The reductions in nitrogen dioxide exposures and emergency room visits were greater for enrollees in goods movement corridors than those in control areas in post-policy years. We found that the goods movement actions were associated with 14.8% (95% CI, -24.0% to -4.4%; P = 0.006) and 11.8% (95% CI, -21.2% to -1.2%; P = 0.030) greater reduction in emergency room visits for the beneficiaries with asthma and chronic obstructive pulmonary disease, respectively, in the third year after California's emission reduction plan.

CONCLUSION

These findings indicate remarkable health benefits via reduced emergency room visits from the significantly improved air quality due to public policy interventions for disadvantaged and susceptible populations.

Leave no one behind: A case of ecosystem service supply equity in Singapore

Urban populations benefit greatly from the ecosystem services provided by urban green and blue spaces. While the equity of provision of and access to urban green and blue spaces has been widely explored, research on equity of ecosystem service provision is relatively scant. Using household level data, our study aims to assess the supply equity of five regulatory ecosystem services in Singapore. We employed linear mixed-effects models and Hot Spot Analysis to analyze their distributional equity across individual households of various demographic characteristics (horizontal inequality), and calculated Gini coefficient for the distribution of PM10 removal service among households categorised into demographic subgroups (vertical inequality). Our results show little evidence of inequitable ecosystem service provision among Singapore's diverse socio-demographic groups. This can be attributed to the early integration of environmental management strategies and meticulous socio-economic desegregation efforts into urban development plans, which maximised provision and maintenance of urban green spaces to all residents.

Disparities in air quality downscaler model uncertainty across socioeconomic and demographic indicators in North Carolina

Studies increasingly use output from the Environmental Protection Agency's Fused Air Quality Surface Downscaler ("downscaler") model, which provides spatial predictions of daily concentrations of fine particulate matter (PM2.5) and ozone (O3) at the census tract level, to study the health and societal impacts of exposure to air pollution. Downscaler outputs have been used to show that lower income and higher minority neighborhoods are exposed to higher levels of PM2.5 and lower levels of O3. However, the uncertainty of the downscaler estimates remains poorly characterized, and it is not known if all subpopulations are benefiting equally from reliable predictions. We examined how the percent errors (PEs) of daily concentrations of PM2.5 and O3 between 2002 and 2016 at the 2010 census tract centroids across North Carolina were associated with measures of racial and educational isolation, neighborhood disadvantage, and urbanicity. Results suggest that there were socioeconomic and demographic disparities in surface concentrations of PM2.5 and O3, as well as their prediction uncertainties. Neighborhoods characterized by less reliable downscaler predictions (i.e., higher PEPM2.5 and PEO3) exhibited greater levels of aerial deprivation as well as educational isolation, and were often non-urban areas (i.e., suburban, or rural). Between 2002 and 2016, predicted PM2.5 and O3 levels decreased and O3 predictions became more reliable. However, the predictive uncertainty for PM2.5 has increased since 2010. Substantial spatial variability was observed in the temporal changes in the predictive uncertainties; educational isolation and neighborhood deprivation levels were associated with smaller increases in predictive uncertainty of PM2.5. In contrast, racial isolation was associated with a greater decline in the reliability of PM2.5 predictions between 2002 and 2016; it was associated with a greater improvement in the predictive reliability of O3 within the same time frame.

Adoption of low-carbon fuels reduces race/ethnicity disparities in air pollution exposure in California

An environmental justice (EJ) analysis shows that adoption of low-carbon energy sources in the year 2050 reduces the race/ethnicity disparity in air pollution exposure in California by as much as 20% for PM_2.5 mass and by as much as 40% for PM_0.1 mass. An ensemble of six different energy scenarios constructed using the energy-economic optimization model CA-TIMES were evaluated in future years. Criteria pollutant emissions were developed for each energy scenario using the CA-REMARQUE model using 4 km spatial resolution over four major geographic areas in California: the greater San Francisco Bay Area including Sacramento (SFBA&SAC), the San Joaquin Valley (SJV), Los Angeles (LA), and San Diego (SD). The Weather Research & Forecasting (WRF) model was used to predict future meteorology fields by downscaling two different climate scenario (RCP4.5 and RCP8.5) generated by two different GCMs (the Community Climate System Model and the Canadian Earth Systems Model). Simulations were performed over 32 weeks randomly selected during the 10 year window from the year 2046 to 2055 to build up a long-term average in the presence of ENSO variability. The trends associated with low-carbon energy adoption were relatively stable across the ensemble of locations and scenarios. Deeper reductions in the carbon intensity of energy sources progressively reduced exposure to PM_2.5 mass and PM_0.1 mass for all California residents. The greater adoption of low-carbon fuels also reduced the racial disparity in the PM exposure. The three energy scenarios that achieved an ~80% reduction in GHG emissions relative to 1990 levels simultaneously produced the greatest reduction in PM exposure for all California residents and the greatest reduction in the racial disparity of that exposure. These findings suggest that the adoption of low-carbon energy can improve public health and reduce racial disparities through an improvement in air quality.

A Bibliometric Analysis on Research Regarding Residential Segregation and Health Based on CiteSpace

Considerable scholarly attention has been directed to the adverse health effects caused by residential segregation. We aimed to visualize the state-of-the-art residential segregation and health research to provide a reference for follow-up studies. Employing the CiteSpace software, we uncovered popular themes, research hotspots, and frontiers based on an analysis of 1211 English-language publications, including articles and reviews retrieved from the Web of Science Core Collection database from 1998 to 2022. The results revealed: (1) The Social Science & Medicine journal has published the most studies. Roland J. Thorpe, Thomas A. LaVeist, Darrell J. Gaskin, David R. Williams, and others are the leading scholars in residential segregation and health research. The University of Michigan, Columbia University, Harvard University, the Johns Hopkins School of Public Health, and the University of North Carolina play the most important role in current research. The U.S. is the main publishing country with significant academic influence. (2) Structural racism, COVID-19, mortality, multilevel modelling, and environmental justice are the top five topic clusters. (3) The research frontier of residential segregation and health has significantly shifted from focusing on community, poverty, infant mortality, and social class to residential environmental exposure, structural racism, and health care. We recommend strengthening comparative research on the health-related effects of residential segregation on minority groups in different socio-economic and cultural contexts.

A benefit allocation model for the joint prevention and control of air pollution in China: In view of environmental justice

The benefit allocation of fair and justice is an inevitable guarantee for the long-term operation of the joint prevention and control of air pollution (JPCAP). The ignorance of interest demands of various governance subjects in the existing benefit allocation mechanism results in the widespread "free rider" behavior in the joint control and unsatisfactory effects of JPCAP. Given this, it is imperative to build a reasonable benefit allocation model. The innovation of this paper is proposing a benefit allocation model of JPCAP to achieve the symmetry between control costs and benefits based on environmental justice. The control objectives and total benefits of JPCAP are calculated through the adjustment of optimal removal rates. The interest demands of various control subjects and benefit compensation scheme are clarified by adopting an improved Shapley method, which comprehensively considers factors affecting environmental justice. An empirical analysis is conducted on SO₂ governance in Beijing-Tianjin-Hebei (BTH) and its surrounding areas. The results show that the benefit allocation model based on environmental justice can not only accurately evaluate the benefits of joint control, but also effectively achieve the symmetry between control costs and benefits. This study provides a scientific and reasonable theoretical basis for the benefit allocation of SO₂ control and can be extended to the researches and practices of other air pollutants control.

The association of racial differences with in-hospital outcomes of patients admitted for sinus node dysfunction

Background

The impact of race and its related social determinants of health on cardiovascular disease outcomes has been well documented. However, limited data exist regarding the association of race with in-hospital outcomes in patients admitted for sinus node dysfunction (SND).

Objective

To evaluate whether racial disparities exist in outcomes for patients hospitalized with a primary diagnosis of SND.

Methods

The National Inpatient Sample was queried from 2011 to 2018 for relevant ICD-9 and ICD-10 diagnosis and procedure codes. Baseline characteristics and in-hospital outcomes in patients with a primary diagnosis of SND were compared among White and non-White patients. A multivariate logistic regression model was used to adjust for potential confounding factors and statistically significant comorbidities between both cohorts.

Results

We identified 655,139 persons admitted with a primary diagnosis of SND, 520,926 (79.5%) of whom were White. Non-White patients had significantly higher all-cause mortality, length of stay, and total hospital cost. There were lower odds of pacemaker insertion (adjusted odds ratio [aOR] 1.13 [95% confidence interval (CI) 1.11–1.15]), temporary transvenous pacing (aOR 1.15 [95% CI 1.11–1.22]), and cardioversion (aOR 1.50 [95% CI 1.42–1.58]) in non-White patients. A subgroup analysis was performed and non-Hispanic Black race was predictive of a decreased odds of pacemaker insertion, cardioversion/defibrillation, and temporary transvenous pacing.

Conclusion

Significant differences of in-hospital outcomes exist between White and non-White patients with SND. These findings appeared to be primarily driven by disparities in non-Hispanic Black patients. Increased recognition and focused efforts to mitigate these disparities will improve the care of underrepresented populations treated for SND.

A Data Mining Approach Reveals Chemicals Detected at Higher Levels in Non-Hispanic Black Women Target Preterm Birth Genes and Pathways

Preterm birth occurs disproportionately in the USA non-Hispanic Black population. Black women also face disproportionate exposure to certain environmental chemicals. The goal of this study was to use publicly available toxicogenomic data to identify chemical exposures that may contribute to preterm birth disparities. We tested 19 chemicals observed at higher levels in the blood or urine of non-Hispanic Black women compared to non-Hispanic White women. We obtained chemical-gene interactions from the Comparative Toxicogenomics Database and a list of genes involved in preterm birth from the Preterm Birth Database. We tested chemicals for enrichment with preterm birth genes using chi-squared tests. We then conducted pathway enrichment analysis for the preterm birth genes using DAVID software and identified chemical impacts on genes involved in these pathways. Genes annotated to all 19 chemicals were enriched with preterm birth genes (FDR-adjusted p value < 0.05). Preterm birth enriched chemicals that were detected at the highest levels in non-Hispanic Black women included methyl mercury, methylparaben, propylparaben, diethyl phthalate, dichlorodiphenyldichloroethylene, and bisphenol S. The preterm birth genes were enriched for pathways including "inflammatory response" (FDR-adjusted p value = 3 × 10-19), "aging" (FDR-adjusted p value = 4 × 10-8) and "response to estradiol" (FDR-adjusted p value = 2 × 10-4). Chemicals enriched with preterm birth genes impacted genes in all three pathways. This study adds to the body of knowledge suggesting that exposures to environmental chemicals contribute to racial disparities in preterm birth and that multiple chemicals drive these effects. These chemicals affect genes involved in biological processes relevant to preterm birth such as inflammation, aging, and estradiol pathways.

Where Is Air Quality Improving, and Who Benefits? A Study of PM2.5 and Ozone Over 15 Years

In the United States, concentrations of criteria air pollutants have declined in recent decades. Questions remain regarding whether improvements in air quality are equitably distributed across subpopulations. We assessed spatial variability and temporal trends in concentrations of particulate matter with an aerodynamic diameter ≤2.5 μm (PM2.5) and ozone (O3) across North Carolina from 2002-2016, and associations with community characteristics. Estimated daily PM2.5 and O3 concentrations at 2010 Census tracts were obtained from the Fused Air Quality Surface Using Downscaling archive and averaged to create tract-level annual PM2.5 and O3 estimates. We calculated tract-level measures of: racial isolation of non-Hispanic Black individuals, educational isolation of non-college educated individuals, the neighborhood deprivation index (NDI), and percentage of the population in urban areas. We fitted hierarchical Bayesian space-time models to estimate baseline concentrations of and time trends in PM2.5 and O3 for each tract, accounting for spatial between-tract correlation. Concentrations of PM2.5 and O3 declined by 6.4 μg/m3 and 13.5 ppb, respectively. Tracts with lower educational isolation and higher urbanicity had higher PM2.5 and more pronounced declines in PM2.5. Racial isolation was associated with higher PM2.5 but not with the rate of decline in PM2.5. Despite declines in pollutant concentrations, over time, disparities in exposure increased for racially and educationally isolated communities.

The breathing human infrastructure: Integrating air quality, traffic, and social media indicators

Outdoor air pollution is a complex system that is responsible for the deaths of millions of people annually, yet the integration of interdisciplinary data necessary to assess air quality's multiple metrics is still lacking. This case study integrates atmospheric indicators (concentrations of criteria pollutants including particulate matter and gaseous pollutants), traffic indicators (permanent traffic monitoring station data), and social indicators (community responses in Twitter archives) representing the interplay of the three critical pillars of the United Nations' Triple Bottom Line: environment, economy, and society. During the watershed moment of the COVID-19 pandemic lockdowns in Florida, urban centers demonstrated the gaps and opportunities for understanding the relationships, through correlations rather than causations, between urban air quality, traffic emissions, and public perceptions. The relationship between the perception and the traffic variables were strongly correlated, however no correlation was observed between the perception and actual air quality indicators, except for NO₂. These observations might consequently infer that traffic serves as people's proxy for air quality, regardless of actual air quality, suggesting that social media messaging around asthma may be a way to monitor traffic patterns in areas where no infrastructure currently exists or is prohibited to build. It also indicates that people are less likely to be reliable sensors to accurately measure air quality due to bias in their observations of traffic volume and/or confirmation biases in broader social discourse. Results presented herein are of significance in demonstrating the capacity for interdisciplinary studies to consider the predictive capacities of social media and air pollution, its use as both lever and indicator of public support for air quality legislation and clean-air transitions, and its ability to overcome limitations of surface monitoring stations.

Environmental Injustices of Leaks from Urban Natural Gas Distribution Systems: Patterns among and within 13 U.S. Metro Areas

Natural gas leaks in local distribution systems can develop as underground pipeline infrastructure degrades over time. These leaks lead to safety, economic, and climate change burdens on society. We develop an environmental justice analysis of natural gas leaks discovered using advanced leak detection in 13 U.S. metropolitan areas. We use Bayesian spatial regression models to study the relationship between the density of leak indications and sociodemographic indicators in census tracts. Across all metro areas combined, we found that leak densities increase with increasing percent people of color and with decreasing median household income. These patterns of infrastructure injustice also existed within most metro areas, even after accounting for housing age and the spatial structure of the data. Considering the injustices described here, we identify actions available to utilities, regulators, and advocacy groups that can be taken to improve the equity of local natural gas distribution systems.

Air pollution exposure disparities in US public housing developments

Fine particulate matter 2.5 microns or less in diameter (PM_2.5) is widely recognized to be a major public health concern. While ethnic/racial minority and lower socioeconomic status individuals in the US experience higher PM_2.5 exposure, previous research on social disparities in PM_2.5 exposure has not examined residents of federally-assisted public housing developments (PHDs). Here we present the first national-scale analysis of the relationship between outdoor PM_2.5 exposure and PHD residency in the US, as well as exposure disparities within the population of households residing in PHDs. We integrated data on average annual PM_2.5 concentrations (2011–2015) with US Department of Housing and Urban Development data on PHDs (2015), and socio-demographic information from the 2011–2015 American Community Survey. Results from multivariable generalized estimating equations indicated that PHD locations, units, and residents are significantly overrepresented in neighborhoods with greater PM_2.5 exposure, after accounting for clustering, urbanization, and other socio-demographic factors. Additionally, significantly higher percentages of Black, Hispanic, disabled, and extremely low-income households reside in PHDs with greater PM_2.5 exposure. Findings represent an important starting point for future research and emphasize the urgent need to identify gaps in environmental, public health, and housing policies that contribute to disproportionate air pollution exposures among PHD residents.

Mapping Mobility: Utilizing Local-Knowledge-Derived Activity Space to Estimate Exposure to Ambient Air Pollution among Individuals Experiencing Unsheltered Homelessness

Individuals experiencing homelessness represent a growing population in the United States. Air pollution exposure among individuals experiencing homelessness has not been quantified. Utilizing local knowledge mapping, we generated activity spaces for 62 individuals experiencing homelessness residing in a semi-rural county within the United States. Satellite derived measurements of fine particulate matter (PM2.5) were utilized to estimate annual exposure to air pollution experienced by our participants, as well as differences in the variation in estimated PM2.5 at the local scale compared with stationary monitor data and point location estimates for the same period. Spatial variation in exposure to PM2.5 was detected between participants at both the point and activity space level. Among all participants, annual median PM2.5 exposure was 16.22 μg/m³, exceeding the National Air Quality Standard. Local knowledge mapping represents a novel mechanism to capture mobility patterns and investigate exposure to air pollution within vulnerable populations. Reliance on stationary monitor data to estimate air pollution exposure may lead to exposure misclassification, particularly in rural and semirural regions where monitoring is limited.

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.

Does air pollution contribute to urban-rural disparity in male lung cancer diseases in China?

It remains unknown whether exposure to ambient air pollution can be a mediator linking socioeconomic indicator to health outcome. The present study aims to examine the mediation effect of PM2.5 air pollution on the association between urban-rural division and the incidence (mortality) rate of male lung cancer. We performed a nationwide analysis in 353 counties (districts) of China between 2006 and 2015. A structural equation model was developed to determine the mediation effect of exposure to PM2.5. We also tested whether the findings of the mediation effect of exposure to PM2.5 are sensitive to the controls of smoking factors and additional air pollutant, and PM2.5 exposures with different lag structures. According to the results, we found that exposure to PM2.5 significantly mediated the association between urban-rural division and the incidence rate of male lung cancer. Specifically, there were significant associations between urban-rural division, exposure to PM2.5, and the incidence rate of male lung cancer, with PM2.5 exposure accounting for 29.80% of total urban-rural difference in incidence rates of male lung cancer. A similar pattern of results was observed for the mortality rate of male lung cancer. That is, there was a significant mediation effect by PM2.5 on the association of the mortality rate with urban-rural division. The findings of exposure to PM2.5 as a mediator were robust in the three sensitivity analyses. In conclusion, urban-rural difference in exposures to PM2.5 may be a potential factor that contributes to urban-rural disparity in male lung cancer diseases in China. The findings inform that air pollution management and control may be effective measures to alleviate the great difference in male lung cancer diseases between urban and rural areas in China.

Selecting Data Analytic and Modeling Methods to Support Air Pollution and Environmental Justice Investigations: A Critical Review and Guidance Framework

Given the serious adverse health effects associated with many pollutants, and the inequitable distribution of these effects between socioeconomic groups, air pollution is often a focus of environmental justice (EJ) research. However, EJ analyses that aim to illuminate whether and how air pollution hazards are inequitably distributed may present a unique set of requirements for estimating pollutant concentrations compared to other air quality applications. Here, we perform a scoping review of the range of data analytic and modeling methods applied in past studies of air pollution and environmental injustice and develop a guidance framework for selecting between them given the purpose of analysis, users, and resources available. We include proxy, monitor-based, statistical, and process-based methods. Upon critically synthesizing the literature, we identify four main dimensions to inform method selection: accuracy, interpretability, spatiotemporal features of the method, and usability of the method. We illustrate the guidance framework with case studies from the literature. Future research in this area includes an exploration of increasing data availability, advanced statistical methods, and the importance of science-based policy.

Uncovering Evidence: Associations between Environmental Contaminants and Disparities in Women's Health

Over the years, industrial accidents and military actions have led to unintentional, large-scale, high-dose human exposure to environmental contaminants with endocrine-disrupting action. These historical events, in addition to laboratory studies, suggest that exposure to toxicants such as dioxins and polychlorinated biphenyls negatively impact the reproductive system and likely influence the development of gynecologic diseases. Although high-level exposure to a single toxicant is rare, humans living in industrialized countries are continuously exposed to a complex mixture of manmade and naturally produced endocrine disruptors, including persistent organic pollutants and heavy metals. Since minorities are more likely to live in areas with known environmental contamination; herein, we conducted a literature review to identify potential associations between toxicant exposure and racial disparities in women's health. Evidence within the literature suggests that the body burden of environmental contaminants, especially in combination with inherent genetic variations, likely contributes to previously observed racial disparities in women's health conditions such as breast cancer, endometriosis, polycystic ovarian syndrome, uterine fibroids, and premature birth.

Assessing Disparity Using Measures of Racial and Educational Isolation

We develop a local, spatial measure of educational isolation (EI) and characterize the relationship between EI and our previously developed measure of racial isolation (RI). EI measures the extent to which non-college educated individuals are exposed primarily to other non-college educated individuals. To characterize how the RI-EI relationship varies across space, we propose a novel measure of local correlation. Using birth records from the State of Michigan (2005–2012), we estimate associations between RI, EI, and birth outcomes. EI was lower in urban communities and higher in rural communities, while RI was highest in urban areas and parts of the southeastern United States (US). We observed greater heterogeneity in EI in low RI tracts, especially in non-urban tracts; residents of high RI tracts are likely to be both educationally and racially isolated. Associations were also observed between RI, EI, and gestational length (weeks) and preterm birth (PTB). For example, moving from the lowest to the highest quintile of RI was associated with a 1.11 (1.07, 1.15) and 1.16 (1.10, 1.22) increase in odds of PTB among NHB and NHW women, respectively. Moving from the lowest to the highest quintile of EI was associated with a 1.07 (1.02, 1.12) and 1.03 (1.00, 1.05) increase in odds of PTB among NHB and NHW women, respectively. This work provides three tools (RI, EI, and the local correlation measure) to researchers and policymakers interested in how residential isolation shapes disparate outcomes.

Explaining the Black-White Disparity in Preterm Birth: A Consensus Statement From a Multi-Disciplinary Scientific Work Group Convened by the March of Dimes

In 2017-2019, the March of Dimes convened a workgroup with biomedical, clinical, and epidemiologic expertise to review knowledge of the causes of the persistent Black-White disparity in preterm birth (PTB). Multiple databases were searched to identify hypothesized causes examined in peer-reviewed literature, 33 hypothesized causes were reviewed for whether they plausibly affect PTB and either occur more/less frequently and/or have a larger/smaller effect size among Black women vs. White women. While definitive proof is lacking for most potential causes, most are biologically plausible. No single downstream or midstream factor explains the disparity or its social patterning, however, many likely play limited roles, e.g., while genetic factors likely contribute to PTB, they explain at most a small fraction of the disparity. Research links most hypothesized midstream causes, including socioeconomic factors and stress, with the disparity through their influence on the hypothesized downstream factors. Socioeconomic factors alone cannot explain the disparity's social patterning. Chronic stress could affect PTB through neuroendocrine and immune mechanisms leading to inflammation and immune dysfunction, stress could alter a woman's microbiota, immune response to infection, chronic disease risks, and behaviors, and trigger epigenetic changes influencing PTB risk. As an upstream factor, racism in multiple forms has repeatedly been linked with the plausible midstream/downstream factors, including socioeconomic disadvantage, stress, and toxic exposures. Racism is the only factor identified that directly or indirectly could explain the racial disparities in the plausible midstream/downstream causes and the observed social patterning. Historical and contemporary systemic racism can explain the racial disparities in socioeconomic opportunities that differentially expose African Americans to lifelong financial stress and associated health-harming conditions. Segregation places Black women in stressful surroundings and exposes them to environmental hazards. Race-based discriminatory treatment is a pervasive stressor for Black women of all socioeconomic levels, considering both incidents and the constant vigilance needed to prepare oneself for potential incidents. Racism is a highly plausible, major upstream contributor to the Black-White disparity in PTB through multiple pathways and biological mechanisms. While much is unknown, existing knowledge and core values (equity, justice) support addressing racism in efforts to eliminate the racial disparity in PTB.

The impact of long- and short-term exposure to different ambient air pollutants on cognitive function in China

In the field of environmental health, the impact of air pollution on people's cognitive function is receiving increasing attention. Various air pollution exposures and different exposure periods result in different degrees of damage to cognition. This paper first used CFPS cognitive tests to evaluate the cognitive function of 15,163 adults in 25 provinces of China. Next, based on the geographical location of the population, the kriging interpolation method was applied to evaluate the different exposure periods for various air pollutants (PM_2.5, NO₂ and O₃). Air pollution exposures lasting 3 years and more were referred to in this paper as long-term exposures, while those lasting<3 years were short-term exposures. This paper used an ordinary least squares (OLS) regression model to explore the differential effects of various air pollutant exposures and discussed the impact of long- and short-term exposure to pollutants. Subsequently, Moran's index was used to test the spatial connection for cognitive function, and the spatial error model was used for analysis in the spatial autoregressive model. This research also conducted a heterogeneity study on the justice of air pollutant exposure among people with different characteristics. The population was classified according to cognitive function and geographic location using OLS regression and quantile regression, and a propensity score matching (PSM) model was used for cross-validation to explore whether people with different characteristics and attributes were differentially exposed to air pollution. We found that there were significant negative relationships between air pollutant exposure and cognitive function, especially PM_2.5 exposure and long-term exposure. In addition, air pollution had significantly different impacts on cognition based on the different characteristics and attributes of the person exposed. This study helps by analyzing the socioeconomic factors that affect the level of exposure and suggests that groups who are vulnerable to environmental pollution should be protected and the occurrence of injustice reduced. The study also provides a reference for the distribution of pollution sources and the allocation of health resources, which can be useful for population distribution planning.

Examining PM2.5 concentrations and exposure using multiple models

Epidemiologic studies have found associations between fine particulate matter (PM_2.5) exposure and adverse health effects using exposure models that incorporate monitoring data and other relevant information. Here, we use nine PM_2.5 concentration models (i.e., exposure models) that span a wide range of methods to investigate i) PM_2.5 concentrations in 2011, ii) potential changes in PM_2.5 concentrations between 2011 and 2028 due to on-the-books regulations, and iii) PM_2.5 exposure for the U.S. population and four racial/ethnic groups. The exposure models included two geophysical chemical transport models (CTMs), two interpolation methods, a satellite-derived aerosol optical depth-based method, a Bayesian statistical regression model, and three data-rich machine learning methods. We focused on annual predictions that were regridded to 12-km resolution over the conterminous U.S., but also considered 1-km predictions in sensitivity analyses. The exposure models predicted broadly consistent PM_2.5 concentrations, with relatively high concentrations on average over the eastern U.S. and greater variability in the western U.S. However, differences in national concentration distributions (median standard deviation: 1.00 μg m^-3) and spatial distributions over urban areas were evident. Further exploration of these differences and their implications for specific applications would be valuable. PM_2.5 concentrations were estimated to decrease by about 1 μg m^-3 on average due to modeled emission changes between 2011 and 2028, with decreases of more than 3 μg m^-3 in areas with relatively high 2011 concentrations that were projected to experience relatively large emission reductions. Agreement among models was closer for population-weighted than uniformly weighted averages across the domain. About 50% of the population was estimated to experience PM_2.5 concentrations less than 10 μg m^-3 in 2011 and PM_2.5 improvements of about 2 μg m^-3 due to modeled emission changes between 2011 and 2028. Two inequality metrics were used to characterize differences in exposure among the four racial/ethnic groups. The metrics generally yielded consistent information and suggest that the modeled emission reductions between 2011 and 2028 would reduce absolute exposure inequality on average.