Inequity in consumption of goods and services adds to racial-ethnic disparities in air pollution exposure

Ambient PM2.5 and specific sources increase inflammatory cytokine responses to stimulators and reduce sensitivity to inhibitors

Ambient exposure to fine particulate matter (PM2.5) is associated with increased morbidity and mortality from multiple diseases. Recent observations suggest the hypothesis that trained immunity contributes to these risks, by demonstrating that ambient PM2.5 sensitizes innate immune cells to mount larger inflammatory response to subsequent bacterial stimuli. However, little is known about how general and durable this sensitization phenomenon is, and whether specific sources of PM2.5 are responsible. Here we consider these issues in a longitudinal study of children. The sample consisted of 277 children (mean age 13.92 years; 63.8% female; 38.4% Black; 32.2% Latinx) who completed baseline visits and were re-assessed two years later. Fasting whole blood was ex vivo incubated with 4 stimulating agents reflecting microbial and sterile triggers of inflammation, and with 2 inhibitory agents, followed by assays for IL-1β, IL-6, IL-8, and TNF-α. Blood also was assayed for 6 circulating biomarkers of low-grade inflammation: C-reactive protein, interleukin-6, -8, and -10, tumor necrosis factor-α, and soluble urokinase-type plasminogen activator receptor. Using machine learning, levels of 15 p.m.2.5 constituents were estimated for a 50 m grid around children's homes. Models were adjusted for age, sex, race, pubertal status, and household income. In cross-sectional analyses, higher neighborhood PM2.5 was associated with larger cytokine responses to the four stimulating agents. These associations were strongest for constituents released by motor vehicles and soil/crustal dust. In longitudinal analyses, residential PM2.5 was associated with declining sensitivity to inhibitory agents; this pattern was strongest for constituents from fuel/biomass combustion and motor vehicles. By contrast, PM2.5 constituents were not associated with the circulating biomarkers of low-grade inflammation. Overall, these findings suggest the possibility of a trained immunity scenario, where PM2.5 heightens inflammatory cytokine responses to multiple stimulators, and dampens sensitivity to inhibitors which counter-regulate these responses.

Portable Air Cleaner Usage and Particulate Matter Exposure Reduction in an Environmental Justice Community: A Pilot Study

Particulate matter (PM) exposure is associated with adverse health outcomes, including respiratory illness. A large fraction of exposure to airborne contaminants occurs in the home. This study, conducted over 5 months in a community with high asthma rates (Chelsea, MA, USA), investigated the use of portable air cleaners (PACs) to reduce indoor PM. Seven asthma-affected households participated, receiving a PAC (Austin Air Health Mate HEPA filter), a QuantAQ sensor to measure PM1, PM2.5, PM10 (µg/m3), and a HOBO plug-load data logger to track PAC usage. Results describe hourly and daily PM concentrations and PAC usage for each household. Hourly average PM concentrations decreased when PACs were turned on (vs. when they were turned off) across households during the study period: PM1 decreased by 0.46 µg/m3, PM2.5 decreased by 0.69 µg/m3, and PM10 decreased by 3.22 µg/m3. PAC usage varied for each household, including constant usage in one household and only usage at certain times of day in others. Higher filtration settings led to lower PM, with significant reductions in some, but not all, homes. Our findings highlight some difficulties in implementing household PAC interventions, yet also provide evidence to support household-level interventions to reduce PM and other indoor sources of air pollution. We also highlight academic-community partnerships as contributing to evidence-based solutions.

Adopting electric school buses in the United States: Health and climate benefits

Electric school buses have been proposed as an alternative to reduce the health and climate impacts of the current U.S. school bus fleet, of which a substantial share are highly polluting old diesel vehicles. However, the climate and health benefits of electric school buses are not well known. As they are substantially more costly than diesel buses, assessing their benefits is needed to inform policy decisions. We assess the health benefits of electric school buses in the United States from reduced adult mortality and childhood asthma onset risks due to exposure to ambient fine particulate matter (PM2.5). We also evaluate climate benefits from reduced greenhouse-gas emissions. We find that replacing the average diesel bus in the U.S. fleet in 2017 with an electric bus yields $84,200 in total benefits. Climate benefits amount to $40,400/bus, whereas health benefits amount to $43,800/bus due to 4.42*10-3 fewer PM2.5-attributable deaths ($40,000 of total) and 7.42*10-3 fewer PM2.5-attributable new childhood asthma cases ($3,700 of total). However, health benefits of electric buses vary substantially by driving location and model year (MY) of the diesel buses they replace. Replacing old, MY 2005 diesel buses in large cities yields $207,200/bus in health benefits and is likely cost-beneficial, although other policies that accelerate fleet turnover in these areas deserve consideration. Electric school buses driven in rural areas achieve small health benefits from reduced exposure to ambient PM2.5. Further research assessing benefits of reduced exposure to in-cabin air pollution among children riding buses would be valuable to inform policy decisions.

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

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

Cumulative Exposures to Environmental and Socioeconomic Risk Factors in Milwaukee County, Wisconsin

The environmental justice literature demonstrates consistently that low-income and minority communities are disproportionately exposed to environmental hazards. In this case study, we examined cumulative multipollutant, multidomain, and multimatrix environmental exposures in Milwaukee County, Wisconsin for the year 2015. We identified spatial hot spots in Milwaukee County both individually (using local Moran's I) and through clusters (using K-means clustering) across a profile of environmental pollutants that span regulatory domains and matrices of exposure, as well as socioeconomic indicators. The cluster with the highest exposures within the urban area was largely characterized by low socioeconomic status and an overrepresentation of the Non-Hispanic Black population relative to the county as a whole. In this cluster, average pollutant concentrations were equivalent to the 78th percentile in county-level blood lead levels, 67th percentile in county-level NO2, 79th percentile in county-level CO, and 78th percentile in county-level air toxics. Simultaneously, this cluster had an average equivalent to the 62nd percentile in county-level unemployment, 70th percentile in county-level population rate lacking a high school diploma, 73rd percentile in county-level poverty rate, and 28th percentile in county-level median household income. The spatial patterns of pollutant exposure and SES indicators suggested that these disparities were not random but were instead structured by socioeconomic and racial factors. Our case study, which combines environmental pollutant exposures, sociodemographic data, and clustering analysis, provides a roadmap to identify and target overburdened communities for interventions that reduce environmental exposures and consequently improve public health.

Development and validation of a race-agnostic computable phenotype for kidney health in adult hospitalized patients

Standard race adjustments for estimating glomerular filtration rate (GFR) and reference creatinine can yield a lower acute kidney injury (AKI) and chronic kidney disease (CKD) prevalence among African American patients than non-race adjusted estimates. We developed two race-agnostic computable phenotypes that assess kidney health among 139,152 subjects admitted to the University of Florida Health between 1/2012-8/2019 by removing the race modifier from the estimated GFR and estimated creatinine formula used by the race-adjusted algorithm (race-agnostic algorithm 1) and by utilizing 2021 CKD-EPI refit without race formula (race-agnostic algorithm 2) for calculations of the estimated GFR and estimated creatinine. We compared results using these algorithms to the race-adjusted algorithm in African American patients. Using clinical adjudication, we validated race-agnostic computable phenotypes developed for preadmission CKD and AKI presence on 300 cases. Race adjustment reclassified 2,113 (8%) to no CKD and 7,901 (29%) to a less severe CKD stage compared to race-agnostic algorithm 1 and reclassified 1,208 (5%) to no CKD and 4,606 (18%) to a less severe CKD stage compared to race-agnostic algorithm 2. Of 12,451 AKI encounters based on race-agnostic algorithm 1, race adjustment reclassified 591 to No AKI and 305 to a less severe AKI stage. Of 12,251 AKI encounters based on race-agnostic algorithm 2, race adjustment reclassified 382 to No AKI and 196 (1.6%) to a less severe AKI stage. The phenotyping algorithm based on refit without race formula performed well in identifying patients with CKD and AKI with a sensitivity of 100% (95% confidence interval [CI] 97%-100%) and 99% (95% CI 97%-100%) and a specificity of 88% (95% CI 82%-93%) and 98% (95% CI 93%-100%), respectively. Race-agnostic algorithms identified substantial proportions of additional patients with CKD and AKI compared to race-adjusted algorithm in African American patients. The phenotyping algorithm is promising in identifying patients with kidney disease and improving clinical decision-making.

Sociodemographic and geographic variation in mortality attributable to air pollution in the United States

There are large differences in premature mortality in the USA by racial/ethnic, education, rurality, and social vulnerability index groups. Using existing concentration-response functions, particulate matter (PM2.5) air pollution, population estimates at the tract level, and county-level mortality data, we estimated the degree to which these mortality discrepancies can be attributed to differences in exposure and susceptibility to PM2.5. We show that differences in mortality attributable to PM2.5 were consistently more pronounced between racial/ethnic groups than by education, rurality, or social vulnerability index, with the Black American population having by far the highest proportion of deaths attributable to PM2.5 in all years from 1990 to 2016. Over half of the difference in age-adjusted all-cause mortality between the Black American and non-Hispanic White population was attributable to PM2.5 in the years 2000 to 2011.

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

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

Toward Heart-Healthy and Sustainable Cities: A Policy Statement From the American Heart Association

Nearly 56% of the global population lives in cities, with this number expected to increase to 6.6 billion or >70% of the world's population by 2050. Given that cardiometabolic diseases are the leading causes of morbidity and mortality in people living in urban areas, transforming cities and urban provisioning systems (or urban systems) toward health, equity, and economic productivity can enable the dual attainment of climate and health goals. Seven urban provisioning systems that provide food, energy, mobility-connectivity, housing, green infrastructure, water management, and waste management lie at the core of human health, well-being, and sustainability. These provisioning systems transcend city boundaries (eg, demand for food, water, or energy is met by transboundary supply); thus, transforming the entire system is a larger construct than local urban environments. Poorly designed urban provisioning systems are starkly evident worldwide, resulting in unprecedented exposures to adverse cardiometabolic risk factors, including limited physical activity, lack of access to heart-healthy diets, and reduced access to greenery and beneficial social interactions. Transforming urban systems with a cardiometabolic health-first approach could be accomplished through integrated spatial planning, along with addressing current gaps in key urban provisioning systems. Such an approach will help mitigate undesirable environmental exposures and improve cardiovascular and metabolic health while improving planetary health. The purposes of this American Heart Association policy statement are to present a conceptual framework, summarize the evidence base, and outline policy principles for transforming key urban provisioning systems to heart-health and sustainability outcomes.

Equity and modeling in sustainability science: Examples and opportunities throughout the process

Equity is core to sustainability, but current interventions to enhance sustainability often fall short in adequately addressing this linkage. Models are important tools for informing action, and their development and use present opportunities to center equity in process and outcomes. This Perspective highlights progress in integrating equity into systems modeling in sustainability science, as well as key challenges, tensions, and future directions. We present a conceptual framework for equity in systems modeling, focused on its distributional, procedural, and recognitional dimensions. We discuss examples of how modelers engage with these different dimensions throughout the modeling process and from across a range of modeling approaches and topics, including water resources, energy systems, air quality, and conservation. Synthesizing across these examples, we identify significant advances in enhancing procedural and recognitional equity by reframing models as tools to explore pluralism in worldviews and knowledge systems; enabling models to better represent distributional inequity through new computational techniques and data sources; investigating the dynamics that can drive inequities by linking different modeling approaches; and developing more nuanced metrics for assessing equity outcomes. We also identify important future directions, such as an increased focus on using models to identify pathways to transform underlying conditions that lead to inequities and move toward desired futures. By looking at examples across the diverse fields within sustainability science, we argue that there are valuable opportunities for mutual learning on how to use models more effectively as tools to support sustainable and equitable futures.

Air pollution exposure may impact the composition of human milk oligosaccharides

Human milk oligosaccharides (HMOs) impact neonate immunity and health outcomes. However, the environmental factors influencing HMO composition remain understudied. This study examined the associations between ambient air pollutant (AAP) exposure and HMOs at 1-month postpartum. Human milk samples were collected at 1-month postpartum (n = 185). AAP (PM2.5, PM10, NO2) exposure included the 9-month pregnancy period through 1-month postpartum. Associations between AAP with (1) HMO diversity, (2) the sum of sialylated and fucosylated HMOs, (3) 6 a priori HMOs linked with infant health, and (4) all HMOs were examined using multivariable linear regression and principal component analysis (PCA). Exposure to AAP was associated with lower HMO diversity. PM2.5 and PM10 exposure was positively associated with the HMO 3-fucosyllactose (3FL); PM2.5 exposure was positively associated with the sum of total HMOs, sum of fucosylated HMOs, and the HMO 2'-fucosyllactose (2'FL). PCA indicated the PM2.5, PM10, and NO2 exposures were associated with HMO profiles. Individual models indicated that AAP exposure was associated with five additional HMOs (LNFP I, LNFP II, DFLNT, LNH). This is the first study to demonstrate associations between AAP and breast milk HMOs. Future longitudinal studies will help determine the long-term impact of AAP on human milk composition.

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.

Electrification of Transit Buses in the United States Reduces Greenhouse Gas Emissions

The transportation sector is the largest emitter of greenhouse gas emissions (GHGs) in the United States. Increased use of public transit and electrification of public transit could help reduce these emissions. The electrification of public transit systems could also reduce air pollutant emissions in densely populated areas, where air pollution disproportionally burdens vulnerable communities with high health impacts and associated social costs. We analyze the life cycle emissions of transit buses powered by electricity, diesel, gasoline, and compressed natural gas and model GHGs and air pollutants mitigated for a transition to a fully electric U.S. public transit bus fleet using transit agency-level data. The electrification of the U.S. bus fleet would reduce several conventional air pollutants and has the potential to reduce transit bus GHGs by 33-65% within the next 14 years depending on how quickly the transition is made and how quickly the electricity grid decarbonizes. A levelized cost of driving analysis shows that with falling capital costs and an increase in annual passenger-kilometers of battery electric buses, the technology could reach levelized cost parity with diesel buses when electric bus capital costs fall below about $670 000 per bus.

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

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

Climate Change and Children's Health: Building a Healthy Future for Every Child

Observed changes in temperature, precipitation patterns, sea level, and extreme weather are destabilizing major determinants of human health. Children are at higher risk of climate-related health burdens than adults because of their unique behavior patterns; developing organ systems and physiology; greater exposure to air, food, and water contaminants per unit of body weight; and dependence on caregivers. Climate change harms children through numerous pathways, including air pollution, heat exposure, floods and hurricanes, food insecurity and nutrition, changing epidemiology of infections, and mental health harms. As the planet continues to warm, climate change's impacts will worsen, threatening to define the health and welfare of children at every stage of their lives. Children who already bear higher burden of disease because of living in low-wealth households and communities, lack of access to high quality education, and experiencing racism and other forms of unjust discrimination bear greater risk of suffering from climate change hazards. Climate change solutions, advanced through collaborative work of pediatricians, health systems, communities, corporations, and governments lead to immediate gains in child health and equity and build a foundation for generations of children to thrive. This technical report reviews the nature of climate change and its associated child health effects and supports the recommendations in the accompanying policy statement on climate change and children's health.

The role of neighborhood deprivation in the cervicovaginal microbiota

BACKGROUND

Lactobacillus-deficient cervicovaginal microbiota is associated with spontaneous preterm birth and is more common among Black individuals. Persistent racial segregation in the United States has led to differential neighborhood exposures by race that can affect pregnancy outcomes. The extent to which neighborhood exposures may explain racial differences in the cervicovaginal microbiota is unknown.

OBJECTIVE

This study aimed to determine whether neighborhood deprivation, defined as material community deprivation, is associated with a Lactobacillus-deficient cervicovaginal microbiota in a prospective cohort of pregnant individuals. Our hypothesis was that racial differences in neighborhood deprivation may explain the higher prevalence of Lactobacillus-deficient cervicovaginal microbiota in Black birthing people.

STUDY DESIGN

This study analyzed data from Motherhood and Microbiome, a prospective pregnancy cohort enrolled from prenatal clinics in a single hospital system 2013-2016 in which a Lactobacillus-deficient cervicovaginal microbiota was previously shown to be associated with spontaneous preterm birth. This study geocoded addresses to obtain census tract neighborhood deprivation data from the Brokamp Nationwide Community Deprivation Index that uses weighted proportions of poverty, income, public assistance, lack of health insurance, and vacant housing. Generalized linear mixed models quantified associations of deprivation with the cervicovaginal microbiota accounting for geographic clustering by census tract and potential confounders. Because of different distributions of neighborhood deprivation and the cervicovaginal microbiota, race-stratified models were used. Mediation analyses quantified the extent to which deprivation may contribute to racial differences in the cervicovaginal microbiota.

RESULTS

Higher neighborhood deprivation was associated with a Lactobacillus-deficient cervicovaginal microbiota. Per standard deviation increment of deprivation, participants had 28% higher adjusted odds (adjusted odds ratio, 1.28; 95% confidence interval, 1.04-1.58) of a Lactobacillus-deficient microbiota. Black participants had higher odds of a Lactobacillus-deficient microbiota than White participants (adjusted odds ratio, 4.00; 95% confidence interval, 2.05-8.26), and mediation analysis revealed that deprivation accounted for 22% (P=.046) of that disparity.

CONCLUSION

Neighborhood deprivation was associated with Lactobacillus-deficient cervicovaginal microbiota and may partially explain Black-White disparities in the cervicovaginal microbiota. Mechanistic studies to explore how environmental exposures modify the cervicovaginal microbiota are warranted to identify novel opportunities for future interventional strategies to prevent preterm birth. As the findings demonstrate a potential biological effect from neighborhood conditions, policies that drive urban planning should be explored to improve pregnancy outcomes.

Health burden from food systems is highly unequal across income groups

Food consumption contributes to the degradation of air quality in regions where food is produced, creating a contrast between the health burden caused by a specific population through its food consumption and that faced by this same population as a consequence of food production activities. Here we explore this inequality within China's food system by linking air-pollution-related health burden from production to consumption, at high levels of spatial and sectorial granularity. We find that low-income groups bear a 70% higher air-pollution-related health burden from food production than from food consumption, while high-income groups benefit from a 29% lower health burden relative to their food consumption. This discrepancy largely stems from a concentration of low-income residents in food production areas, exposed to higher emissions from agriculture. Comprehensive interventions targeting both production and consumption sides can effectively reduce health damages and concurrently mitigate associated inequalities, while singular interventions exhibit limited efficacy.

A multi-scale lifecycle and technoeconomic framework for higher education fleet electrification

Transportation accounts for one-quarter of all energy related greenhouse gas emissions. As it pertains to transport electrification, higher education institutions-such as universities-can model solutions that affect broader society. Despite this, higher education's role in fleet electrification adoption has been understudied. We, therefore, modeled an archetypical higher education institution to analyze the carbon and economic payback periods of three electrification scenarios (Business-as-Usual, Targeted Electrification, and Full Electrification) using a cradle-to-grave lifecycle and technoeconomic approach. Given the archetypical higher education institution fleet of 368 vehicles, results show an economic ratio plateau point of about 8 years at 20 fuel-based cars replaced by electric vehicles and a carbon payback period peak of roughly 10 months at 50 fuel-based cars replaced. We then performed a multi-scalar analysis by leveraging implementation theory. We find that higher education institutions that adhere to the tenets of implementation theory are poised to be pro-environmental change agents in many regions and countries. The methods and findings herein can be adapted to other institutions, regardless of fleet size, and can bolster relevant decision-making outcomes now.

The Impact of Climate Change on Global Oncology

Climate change is the greatest threat to human health of our time, with significant implications for global cancer control efforts. The changing frequency and behavior of climate-driven extreme weather events results in more frequent and increasingly unanticipated disruptions in access to cancer care. Given the significant threat that climate change poses to cancer control efforts, oncology professionals should champion initiatives that help protect the health and safety of patients with cancer, such as enhancing emergency preparedness and response efforts and reducing emissions from our own professional activities, which has health cobenefits for the entire population.

Climate and environmental changes exacerbate health disparities in pregnant people and their offspring. How can we protect women and their babies?

BACKGROUND

The effects of climate and environmental changes (CEC) are being felt globally and will worsen over the next decade unless significant changes are made on a global level. Climate change is having serious consequences for health, particularly for vulnerable women and their offspring and less resilient individuals in communities with socioeconomic inequalities. To protect human health from CEC effects, efforts need to be directed toward building resilience strategies. Building political and economic power, as well as directly addressing CEC-related challenges, are critical components of climate resilience. Effective communication and tailored methods to engage women in preventive strategies are also necessary to ameliorate the deleterious effects of CEC on women's health. Furthermore, women from marginalized communities face more CEC-associated challenges.

CONCLUSIONS

Therefore, effective policies and programs targeting these at-risk populations-are crucial to improve the overall state of global health. In closing, it is time to increase awareness of the effects of CECs on women's health and their transgenerational effects in order to ensure that all people, regardless of race, ethnicity, education and income are protected from the detrimental effects of CECs.

Dynamic Traffic Data in Machine-Learning Air Quality Mapping Improves Environmental Justice Assessment

Air pollution poses a critical public health threat around many megacities but in an uneven manner. Conventional models are limited to depict the highly spatial- and time-varying patterns of ambient pollutant exposures at the community scale for megacities. Here, we developed a machine-learning approach that leverages the dynamic traffic profiles to continuously estimate community-level year-long air pollutant concentrations in Los Angeles, U.S. We found the introduction of real-world dynamic traffic data significantly improved the spatial fidelity of nitrogen dioxide (NO2), maximum daily 8-h average ozone (MDA8 O3), and fine particulate matter (PM2.5) simulations by 47%, 4%, and 15%, respectively. We successfully captured PM2.5 levels exceeding limits due to heavy traffic activities and providing an "out-of-limit map" tool to identify exposure disparities within highly polluted communities. In contrast, the model without real-world dynamic traffic data lacks the ability to capture the traffic-induced exposure disparities and significantly underestimate residents' exposure to PM2.5. The underestimations are more severe for disadvantaged communities such as black and low-income groups, showing the significance of incorporating real-time traffic data in exposure disparity assessment.

Corridor-Level Impacts of Battery-Electric Heavy-Duty Trucks and the Effects of Policy in the United States

Electrifying freight trucks will be key to alleviating air pollution burdens on disadvantaged communities and mitigating climate change. The United States plans to pursue this aim by adding vehicle charging infrastructure along specific freight corridors. This study explores the coevolution of the electricity grid and freight trucking landscape using an integrated assessment framework to identify when each interstate and drayage corridor becomes advantageous to electrify from a climate and human health standpoint. Nearly all corridors achieve greenhouse gas emission reductions if electrified now. Most can reduce health impacts from air pollution if electrified by 2040 although some corridors in the Midwest, South, and Mid-Atlantic regions remain unfavorable to electrify from a human health standpoint, absent policy support. Recent policy, namely, the Inflation Reduction Act, accelerates this timeline to 2030 for most corridors and results in net human health benefits on all corridors by 2050, suggesting that near-term investments in truck electrification, particularly drayage corridors, can meaningfully reduce climate and health burdens.

Public Health Benefits From Improved Identification of Severe Air Pollution Events With Geostationary Satellite Data

Despite improvements in ambient air quality in the US in recent decades, many people still experience unhealthy levels of pollution. At present, national-level alert-day identification relies predominately on surface monitor networks and forecasters. Satellite-based estimates of surface air quality have rapidly advanced and have the capability to inform exposure-reducing actions to protect public health. At present, we lack a robust framework to quantify public health benefits of these advances in applications of satellite-based atmospheric composition data. Here, we assess possible health benefits of using geostationary satellite data, over polar orbiting satellite data, for identifying particulate air quality alert days (24hr PM2.5 > 35 μg m-3) in 2020. We find the more extensive spatiotemporal coverage of geostationary satellite data leads to a 60% increase in identification of person-alerts (alert days × population) in 2020 over polar-orbiting satellite data. We apply pre-existing estimates of PM2.5 exposure reduction by individual behavior modification and find these additional person-alerts may lead to 1,200 (800-1,500) or 54% more averted PM2.5-attributable premature deaths per year, if geostationary, instead of polar orbiting, satellite data alone are used to identify alert days. These health benefits have an associated economic value of 13 (8.8-17) billion dollars ($2019) per year. Our results highlight one of many potential applications of atmospheric composition data from geostationary satellites for improving public health. Identifying these applications has important implications for guiding use of current satellite data and planning future geostationary satellite missions.

Structural Racism and Lung Cancer Risk: A Scoping Review

Importance

Structural racism is associated with persistent inequities in health and health outcomes in the US for racial and ethnic minority groups. This review summarizes how structural racism contributes to differential population-level exposure to lung cancer risk factors and thus disparate lung cancer risk across different racial and ethnic groups.

Observations

A scoping review was conducted focusing on structural racism and lung cancer risk for racial and ethnic minority groups. The domains of structural racism evaluated included housing and built environment, occupation and employment, health care, economic and educational opportunity, private industry, perceived stress and discrimination, and criminal justice involvement. The PubMed, Embase, and MedNar databases were searched for English-language studies in the US from January 1, 2010, through June 30, 2022. The review demonstrated that racial and ethnic minority groups are more likely to have environmental exposures to air pollution and known carcinogens due to segregation of neighborhoods and poor housing quality. In addition, racial and ethnic minority groups were more likely to have exposures to pesticides, silica, and asbestos secondary to higher employment in manual labor occupations. Furthermore, targeted marketing and advertisement of tobacco products by private industry were more likely to occur in neighborhoods with more racial and ethnic minority groups. In addition, poor access to primary care services and inequities in insurance status were associated with elevated lung cancer risk among racial and ethnic minority groups. Lastly, inequities in tobacco use and cessation services among individuals with criminal justice involvement had important implications for tobacco use among Black and Hispanic populations.

Conclusions and Relevance

The findings suggest that structural racism must be considered as a fundamental contributor to the unequal distribution of lung cancer risk factors and thus disparate lung cancer risk across different racial and ethnic groups. Additional research is needed to better identify mechanisms contributing to inequitable lung cancer risk and tailor preventive interventions.

Advancing the community health vulnerability index for wildland fire smoke exposure

Wildland fire smoke risks are not uniformly distributed across people and places, and the most vulnerable communities are often disproportionately impacted. This study develops a county level community health vulnerability index (CHVI) for the Contiguous United States (CONUS) using three major vulnerability components: adaptive capacity, sensitivity, and exposure at the national and regional level. We first calculated sensitivity and adaptive capacity sub-indices using nine sensitivity and twenty adaptive capacity variables. These sub-indices were then combined with an exposure sub-index, which is based on the Community Multiscale Air Quality data (2008-2018), to develop CHVI. Finally, we conducted several analyses with the derived indices to: 1) explore associations between the level of fine particulate matter from wildland fires (fire-PM2.5) and the sub-indices/CHVI; 2) measure the impact of fire-PM2.5 on the increase in the annual number of days with 12-35 μg/m3 (moderate) and >35 μg/m3 (at or above unhealthy for sensitive groups) based on the US EPA Air Quality Index categories, and 3) calculate population size in different deciles of the sub-indices/CHVI. This study has three main findings. First, we showed that the counties with higher daily fire-PM2.5 concentration tend to have lower adaptive capacity and higher sensitivity and vulnerability. Relatedly, the counties at high risk tended to experience a greater increase in the annual number of days with 12-35 μg/m3 and >35 μg/m3 than their counterparts. Second, we found that 16.1, 12.0, and 17.6 million people out of 332 million in CONUS reside in the counties in the lowest adaptive capacity decile, highest sensitivity decile, and highest vulnerability decile, respectively. Third, we identified that the US Northwest, California, and Southern regions tended to have higher vulnerability than others. Accurately identifying a community's vulnerability to wildfire smoke can help individuals, researchers, and policymakers better understand, prepare for, and respond to future wildland fire events.

All-Cause NO2-Attributable Mortality Burden and Associated Racial and Ethnic Disparities in the United States

Nitrogen dioxide (NO2) is a regulated pollutant that is associated with numerous health impacts. Recent advances in epidemiology indicate high confidence linking NO2 exposure with increased mortality, an association that recent studies suggest persists even at concentrations below regulatory thresholds. While large disparities in NO2 exposure among population subgroups have been reported, U.S. NO2-attributable mortality rates and their disparities remain unquantified. Here we provide the first estimate of NO2-attributable all-cause mortality across the contiguous U.S. (CONUS) at the census tract-level. We leverage fine-scale, satellite-informed, land use regression model NO2 concentrations and census tract-level baseline mortality data to characterize the associated disparities among different racial/ethnic subgroups. Across CONUS, we estimate that the NO2-attributable all-cause mortality is ∼170,850 (95% confidence interval: 43,970, 251,330) premature deaths yr-1 with large variability across census tracts and within individual cities. Additionally, we find that higher NO2 concentrations and underlying susceptibilities for predominately Black communities lead to NO2-attributable mortality rates that are ∼47% higher compared to CONUS-wide average rates. Our results highlight the substantial U.S. NO2 mortality burden, particularly in marginalized communities, and motivate adoption of more stringent standards to protect public health.

Exploring Regional Reduction Pathways for Human Exposure to Fine Particulate Matter (PM2.5) Using a Traffic Assignment Model

An exposure-based traffic assignment (TA) model is used to quantify primary and secondary fine particulate matter (PM2.5) exposure from on-road vehicle flow on the Chicago Metropolitan Area regional network. PM2.5 exposure due to emissions from light-duty vehicles, heavy-duty trucks, public transportation, and electricity generation for electric vehicle charging and light-rail transportation is considered. The model uses travel demand data disaggregated by time-of-day period and vehicle user class to compare the exposure impacts of two TA optimization scenarios: a baseline user equilibrium with respect to travel time (UET) and a system optimal with respect to pollutant intake (SOI). Estimated baseline PM2.5 exposure damages are $3.7B-$8.3B/year. The SOI uses exposure-based vehicle rerouting to reduce total damages by 8.2%, with high-impacted populations benefiting from 10% to 20% reductions. However, the SOI's rerouting principle leads to a 66% increase in travel time. The model is then used to quantify the mitigation potential of different exposure reduction strategies, including a bi-objective optimization formulation that minimizes travel time and PM2.5 exposure concurrently, adoption of a cleaner vehicle fleet, higher public transportation use, particle filtration, and exposure-based truck routing. Exposure reductions range between 1% and 40%, but collective adoption of all strategies would lead to reductions upward of 50%.

Community-Based Strategies to Reduce Alzheimer's Disease and Related Dementia Incidence Among Rural, Racially/Ethnically Diverse Older Adults

Purpose of Review

The purpose of this paper was to address the research question "What recent advances in Alzheimer's Disease and Related Dementias (ADRD) risk reduction strategies can be tailored for rural, racially/ethnically diverse populations?" A rural resident's life story that grounded the work is shared. Next, a brief description is provided regarding ADRD risk factors of importance in rural, multicultural settings. Gaps in U.S.-based research are highlighted. Policy actions and interventions that may make a difference in alleviating rural, ADRD-related disparities are offered.

Recent Findings

More than a dozen factors, including lack of built environment, periodontitis, poor air quality, and sensory loss, were identified that are of particular relevance to rural groups. Evidence of importance to underserved residents has also emerged regarding the harmful effects of ultra-processed foods on brain health, benefits of even minimal physical activity, and importance of social engagement, on brain health.

Summary

Resident-led initiatives will be key to creating change at the community level. Health providers are also called to assist in identifying and adapting culturally specific upstream approaches, in partnership with community stakeholders. These mechanisms are vital for decreasing ADRD burdens in underserved communities facing the largest disparities in preventive care.

The impact of air pollution on neurocognitive development: Adverse effects and health disparities

Air pollution is recognized as a major public health concern. The number of deaths related to ambient air pollution has increased in recent years and is projected to continue rising. Additionally, both short- and long-term air pollution exposure has been linked with deleterious effects on neurocognitive function and development. While air pollution poses as a threat to everyone, people of color and individuals of lower socioeconomic status are often exposed to elevated levels of air pollution as a function of systemic racism and classism. Further, given additional disparities in access to healthcare and other compounding stressors, adverse effects of air pollution on neurocognitive health are exacerbated among individuals who hold marginalized identities-making effects both less likely to be detected and treated. This review examines evidence of the effects of air pollution on neurocognitive development across the lifespan and incorporates an environmental justice perspective to highlight disparities in air pollution exposure across race and socioeconomic status. Last, upon the reviewed evidence, limitations of past research and recommendations for policy are discussed.

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

BACKGROUND

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

OBJECTIVE

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

DISCUSSION

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

The impact of air pollution on asthma: clinical outcomes, current epidemiology, and health disparities

INTRODUCTION

Air pollution has been shown to have a significant impact on morbidity and mortality of respiratory illnesses including asthma.

AREAS COVERED

Outdoor air pollution consists of a mixture of individual pollutants including vehicle traffic and industrial pollution. Studies have implicated an array of individual components of air pollution, with PM2.5, NO2, SO2, and ozone being the most classically described, and newer literature implicating other pollutants such as black carbon and volatile organic compounds. Epidemiological and cohort studies have described incidence and prevalence of pollution-related asthma and investigated both acute and chronic air pollution exposure as they relate to asthma outcomes. There is an increasing body of literature tying disparities in pollution exposure to clinical outcomes. In this narrative review, we assessed the published research investigating the association of pollution with asthma outcomes, focusing on the adult population and health care disparities.

EXPERT OPINION

Pollution has multiple deleterious effects on respiratory health but there is a lack of data on individualized pollution monitoring, making it difficult to establish a temporal relationship between exposure and symptoms, thereby limiting our understanding of safe exposure levels. Future research should focus on more personalized monitoring and treatment plans for mitigating exposure.

Mortality risk from United States coal electricity generation

Policy-makers seeking to limit the impact of coal electricity-generating units (EGUs, also known as power plants) on air quality and climate justify regulations by quantifying the health burden attributable to exposure from these sources. We defined "coal PM2.5" as fine particulate matter associated with coal EGU sulfur dioxide emissions and estimated annual exposure to coal PM2.5 from 480 EGUs in the US. We estimated the number of deaths attributable to coal PM2.5 from 1999 to 2020 using individual-level Medicare death records representing 650 million person-years. Exposure to coal PM2.5 was associated with 2.1 times greater mortality risk than exposure to PM2.5 from all sources. A total of 460,000 deaths were attributable to coal PM2.5, representing 25% of all PM2.5-related Medicare deaths before 2009 and 7% after 2012. Here, we quantify and visualize the contribution of individual EGUs to mortality.

Fine particulate matter composition in American Indian vs. Non-American Indian communities

BACKGROUND

Fine particulate matter (PM2.5) exposure is a known risk factor for numerous adverse health outcomes, with varying estimates of component-specific effects. Populations with compromised health conditions such as diabetes can be more sensitive to the health impacts of air pollution exposure. Recent trends in PM2.5 in primarily American Indian- (AI-) populated areas examined in previous work declined more gradually compared to the declines observed in the rest of the US. To further investigate components contributing to these findings, we compared trends in concentrations of six PM2.5 components in AI- vs. non-AI-populated counties over time (2000-2017) in the contiguous US.

METHODS

We implemented component-specific linear mixed models to estimate differences in annual county-level concentrations of sulfate, nitrate, ammonium, organic matter, black carbon, and mineral dust from well-validated surface PM2.5 models in AI- vs. non-AI-populated counties, using a multi-criteria approach to classify counties as AI- or non-AI-populated. Models adjusted for population density and median household income. We included interaction terms with calendar year to estimate whether concentration differences in AI- vs. non-AI-populated counties varied over time.

RESULTS

Our final analysis included 3108 counties, with 199 (6.4%) classified as AI-populated. On average across the study period, adjusted concentrations of all six PM2.5 components in AI-populated counties were significantly lower than in non-AI-populated counties. However, component-specific levels in AI- vs. non-AI-populated counties varied over time: sulfate and ammonium levels were significantly lower in AI- vs. non-AI-populated counties before 2011 but higher after 2011 and nitrate levels were consistently lower in AI-populated counties.

CONCLUSIONS

This study indicates time trend differences of specific components by AI-populated county type. Notably, decreases in sulfate and ammonium may contribute to steeper declines in total PM2.5 in non-AI vs. AI-populated counties. These findings provide potential directives for additional monitoring and regulations of key emissions sources impacting tribal lands.

To promote healthy aging, focus on the environment

To build health equity for an aging world marked by dramatic disparities in healthy lifespan between countries, regions and population groups, research at the intersections of biology, toxicology and the social and behavioral sciences points the way: to promote healthy aging, focus on the environment. In this Perspective, we suggest that ideas and tools from the emerging field of geroscience offer opportunities to advance the environmental science of aging. Specifically, the capacity to measure the pace and progress of biological processes of aging within individuals from relatively young ages makes it possible to study how changing environments can change aging trajectories from early in life, in time to prevent or delay aging-related disease and disability and build aging health equity.

Prevalence and predictors of wind energy opposition in North America

Addressing climate change requires societies to transition away from fossil fuels toward low-carbon energy, including renewables. Unfortunately, large wind projects have proven politically controversial, with groups opposing them across advanced economies. To date, there are few large-scale, systematic studies to identify the prevalence and predictors of opposition to wind energy projects. Here, we analyzed a dataset of wind energy projects across the United States and Canada between 2000 and 2016. We found that during this period, in the United States, 17% of wind projects faced significant opposition, and in Canada, 18% faced opposition, with rates in both countries growing over time. Opposition was concentrated regionally in the Northeastern United States and in Ontario, Canada. In both countries, larger projects with more turbines were more likely to be opposed. In the United States, opposition was more likely and more intense in areas with a higher proportion of White people, and a smaller proportion of Hispanic people. In Canada, opposition was more likely and more intense in wealthier communities. The most common tactics used to oppose wind energy were court cases, legislation, and physical protests. The number of people engaging in opposition to wind projects is likely small: Across articles that cited the number of individuals engaging in protests, the median number was 23 in the United States and 34 in Canada. When wealthier, Whiter communities oppose wind projects, this slows down the transition away from fossil fuel projects in poorer communities and communities of color, an environmental injustice we call "energy privilege."

Association between Outdoor Light at Night and Prostate Cancer in the Health Professionals Follow-up Study

BACKGROUND

Circadian disruption is a potential risk factor for advanced prostate cancer, and light at night (LAN) exposure may disrupt circadian rhythms. We evaluated whether outdoor LAN increases the risk of prostate cancer.

METHODS

We prospectively followed 49,148 participants in the Health Professionals Follow-up Study from 1986 through 2016. We estimated baseline and cumulative time-varying outdoor LAN with ∼1 km2 resolution using data from the US Defense Meteorological Satellite Program's Operational Linescan System, which was assigned to participants' geocoded addresses. Participants reside in all 50 U.S. states and reported a work or home address. We used multivariable Cox models to estimate HRs and 95% confidence intervals (CI) for the association between outdoor LAN and risk of overall (7,175 cases) and fatal (915 cases) prostate cancer adjusting for individual and contextual factors.

RESULTS

There was no association between the interquartile range increase in cumulative LAN and total (HR, 1.02; 95% CI, 0.98-1.06) or fatal (HR, 1.05; 95% CI, 0.96-1.15) prostate cancer in adjusted models. However, there was a positive association between baseline LAN and total prostate cancer among non-movers (HR, 1.06; 95% CI, 1.00-1.14) including among highly screened participants (HR, 1.11; 95% CI, 1.01-1.23).

CONCLUSIONS

There was a suggestive positive association between baseline outdoor LAN and total prostate cancer. Additional studies with different measures of outdoor LAN and in more diverse populations are necessary.

IMPACT

To our knowledge, this is the first longitudinal cohort study exploring the relationship between outdoor LAN and prostate cancer.

Place-Based Strategies Addressing Neighborhood Environments to Improve Perinatal and Preterm Infant Outcomes

Preterm birth (defined as birth <37 weeks of gestation) is a significant health concern globally, with lasting implications for individuals, families, and society. In the United States, high preterm birth rates among Black and low-income populations likely result from differences in environmental exposures. Structural racism and economic disadvantage have led to unequal distribution of polluting industrial sites and roadways across society as well as differential access to health-promoting resources which contribute to preterm birth risk. Once born, preterm infants remain at risk for numerous environmentally responsive adverse health outcomes that affect growth and development throughout childhood and adulthood. In this commentary, we describe associations of neighborhood environments with pregnancy and preterm infant health outcomes and propose strategies to address harmful exposures that affect families across the lifespan.

Managing nitrogen in maize production for societal gain

Highly productive agriculture is essential to feed humanity, but agricultural practices often harm human health and the environment. Using a nitrogen (N) mass-balance model to account for N inputs and losses to the environment, along with empirical based models of yield response, we estimate the potential gains to society from improvements in nitrogen management that could reduce health and environmental costs from maize grown in the US Midwest. We find that the monetized health and environmental costs to society of current maize nitrogen management practices are six times larger than the profits earned by farmers. Air emissions of ammonia from application of synthetic fertilizer and manure are the largest source of pollution costs. We show that it is possible to reduce these costs by 85% ($21.6 billion per year, 2020$) while simultaneously increasing farmer profits. These gains come from (i) managing fertilizer ammonia emissions by changing the mix of fertilizer and manure applied, (ii) improving production efficiency by reducing fertilization rates, and (iii) halting maize production on land where health and environmental costs exceed farmer profits, namely on low-productivity land and locations in which emissions are especially harmful. Reducing ammonia emissions from changing fertilizer types-in (i)-reduces health and environmental costs by 46% ($11.7 billion). Reducing fertilization rates-in (ii)-limits nitrous oxide emissions, further reducing health and environmental costs by $9.5 billion, and halting production on 16% of maize-growing land in the Midwest-in (iii)-reduces costs by an additional $0.4 billion.

Associations of neighborhood social vulnerability with emergency department visits and readmissions among infants with bronchopulmonary dysplasia

OBJECTIVES

To characterize associations of the CDC Social Vulnerability Index (SVI) with medically attended acute respiratory illness among infants with bronchopulmonary dysplasia (BPD).

STUDY DESIGN

Retrospective cohort of 378 preterm infants with BPD from a single center. Multivariable logistic regression quantified associations of SVI with medically attended acute respiratory illness, defined as emergency department (ED) visits or hospital readmissions within a year after first hospital discharge. Mediation analysis quantified the extent to which differences in SVI may explain known Black-White disparities in medically attended acute respiratory illness.

RESULTS

SVI was associated with medically attended respiratory illness (per SVI standard deviation increment, aOR 1.44, 95% CI: 1.17-1.78). Adjustment for race and ethnicity attenuated the association (aOR 1.27, 95% CI: 0.97-1.64). SVI significantly mediated 31% of the Black-White disparity in ED visits (p = 0.04).

CONCLUSIONS

SVI was associated with, and may partially explain racial disparities in, medically attended acute respiratory illness among infants with BPD.

Air pollution health burden embodied in China's supply chains

Product trade plays an increasing role in relocating production and the associated air pollution impact among sectors and regions. While a comprehensive depiction of atmospheric pollution redistribution through trade chains is missing, which may hinder targeted clean air cooperation among sectors and regions. Here, we combined five state-of-the-art models from physics, economy, and epidemiology to track the anthropogenic fine particle matters (PM_2.5) related premature mortality along the supply chains within China in 2017. Our results highlight the key sectors that affect PM_2.5-related mortality from both production and consumption perspectives. The consumption-based effects from food, light industry, equipment, construction, and services sectors, caused 2-22 times higher deaths than those from a production perspective and totally contributed 63% of the national total. From a cross-boundary perspective, 25.7% of China's PM_2.5-related deaths were caused by interprovincial trade, with the largest transfer occurring from the central and northern regions to well-developed east coast provinces. Capital investment dominated the cross-boundary effect (56% of the total) by involving substantial equipment and construction products, which greatly rely on product exports from regions with specific resources. This supply chain-based analysis provides a comprehensive quantification and may inform more effective joint-control efforts among associated regions and sectors from a health risk perspective.

Air quality related equity implications of U.S. decarbonization policy

Climate policies that target greenhouse gas emissions can improve air quality by reducing co-emitted air pollutant emissions. However, the extent to which climate policy could contribute to the targets of reducing existing pollution disparities across different populations remains largely unknown. We quantify potential air pollution exposure reductions under U.S. federal carbon policy, considering implications of resulting health benefits for exposure disparities across U.S. racial/ethnic groups. We focus on policy cases that achieve reductions of 40-60% in 2030 economy-wide carbon dioxide (CO2) emissions, when compared with 2005 emissions. The 50% CO2 reduction policy case reduces average fine particulate matter (PM2.5) exposure across racial/ethnic groups, with greatest benefit for non-Hispanic Black (-0.44 μg/m3) and white populations (-0.37 μg/m3). The average exposure disparity for racial/ethnic minorities rises from 12.4% to 13.1%. Applying an optimization approach to multiple emissions reduction scenarios, we find that no alternate combination of reductions from different CO2 sources would substantially mitigate exposure disparities. Results suggest that CO2-based strategies for this range of reductions are insufficient for fully mitigating PM2.5 exposure disparities between white and racial/ethnic minority populations; addressing disparities may require larger-scale structural changes.

Impact of exposure to air pollution on cervicovaginal microbial communities

PURPOSE

Vaginal microbial communities can be dominated by anaerobic (community state type IV, CST IV) or Lactobacillus (other CSTs) species. CST IV is a risk factor for spontaneous preterm birth (sPTB) and is more common among Black than White populations. In the US, average air pollution exposures are higher among Black compared to White people and exert systemic health effects. We sought to (1) quantify associations of air pollution, specifically particulate matter <2.5 μm in diameter (PM2.5), with CST IV and (2) explore the extent to which racial disparities in PM2.5 exposure might explain racial differences in the prevalence of CST IV.

DESIGN

Methods: We performed a secondary analysis of 566 participants of the Motherhood & Microbiome study. PM2.5 exposures were derived from a machine learning model integrating NASA satellite and EPA ground monitor data. Previously, cervicovaginal swabs from 15 to 20 weeks' gestation were analyzed using 16 S rRNA sequencing and hierarchical clustering assigned CSTs. Multivariable logistic regression models calculated adjusted odds ratios of CST IV (vs. other CSTs) per interquartile range (IQR) increment of PM2.5. Race-stratified and mediation analyses were performed.

RESULTS

Higher PM2.5 exposure was associated with CST IV (aOR 1.39, 95% CI 1.02-1.91). Further adjustment for race/ethnicity attenuated the association (aOR 1.34, 95% CI: 0.97-1.83). Black participants (vs. White) had higher median PM2.5 exposure (10.6 vs. 9.6 μg/m3, P < 0.001) and higher prevalence of CST IV (47% vs. 11%, P < 0.001). Mediation analysis revealed that higher PM2.5 exposure may explain 3.9% (P = 0.038) and 3.3% (P = 0.15) of the Black-White disparity in CST IV in unadjusted and adjusted models, respectively.

CONCLUSION

PM2.5 was associated with CST IV, a risk factor for sPTB. Additionally, PM2.5 exposure may partially explain racial differences in the prevalence of CST IV. Further research is warranted to discover how environmental exposures affect microbial composition and perpetuate racial health disparities.

Machine learning approaches reveal highly heterogeneous air quality co-benefits of the energy transition

Estimating health benefits of reducing fossil fuel use from improved air quality provides important rationales for carbon emissions abatement. Simulating pollution concentration is a crucial step of the estimation, but traditional approaches often rely on complicated chemical transport models that require extensive expertise and computational resources. In this study, we develop a machine learning framework that is able to provide precise and robust annual average fine particle (PM2.5) concentration estimations directly from a high-resolution fossil energy use dataset. Applications of the framework with Chinese data reveal highly heterogeneous health benefits of avoiding premature mortality by reducing fossil fuel use in different sectors and regions in China with a mean of $19/tCO2 and a standard deviation of $38/tCO2. Reducing rural and residential coal use offers the highest co-benefits with a mean of $151/tCO2. Our findings prompt careful policy designs to maximize cost-effectiveness in the transition toward a carbon-neutral energy system.

Human milk EV-miRNAs: a novel biomarker for air pollution exposure during pregnancy

Exposure to ambient and near-roadway air pollution during pregnancy has been linked with several adverse health outcomes for pregnant women and their babies. Emerging research indicates that microRNA (miRNA) expression can be altered by exposure to air pollutants in a variety of tissues. Additionally, miRNAs from breast tissue and circulating miRNAs have previously been proposed as a biomarker for breast cancer diagnosis and prognosis. Therefore, this study sought to evaluate the associations between pregnancy exposures to ambient (PM10, PM2.5, NO2, O3) and near-roadway air pollution (total NOx, freeway NOx, non-freeway NOx) with breast milk extracellular vesicle miRNA (EV-miRNA), measured at 1-month postpartum, in a cohort of 108 Latina women living in Southern California. We found that PM10 exposure during pregnancy was positively associated with hsa-miR-200c-3p, hsa-miR-200b-3p, and hsa-let-7c-5p, and was negatively associated with hsa-miR-378d. We also found that pregnancy PM2.5 exposure was positively associated with hsa-miR-200c-3p and hsa-miR-200b-3p. First and second trimester exposure to PM10 and PM2.5 was associated with several EV-miRNAs with putative messenger RNA targets related to cancer. This study provides preliminary evidence that air pollution exposure during pregnancy is associated with human milk EV-miRNA expression.

Modeling and Analysis of Air Pollution and Environmental Justice: The Case for North Carolina's Hog Concentrated Animal Feeding Operations

BACKGROUND

Concentrated animal feeding operations (CAFOs) emit pollutants that can cause negative impacts on human health. The concentration of hog production in North Carolina raises concerns regarding the disproportionate exposure of vulnerable communities to air pollution from CAFOs.

OBJECTIVES

We investigated whether exposure to gaseous ammonia (NH 3 ) and hydrogen sulfide (H 2 S ) (in 2019) differs between subpopulations by examining demographics, including race/ethnicity, age, educational attainment, language proficiency, and socioeconomic status.

METHODS

We used an Air Monitoring Station (AMS)/Environmental Protection Agency (EPA) Regulatory Model (AERMOD)-based Human Exposure Model (version 3) to estimate ambient concentrations of NH 3 and H 2 S from hog farms in Duplin County and its surrounding counties in North Carolina and estimate subsequent exposures of communities within 50 km of Duplin County, North Carolina, or the Duplin County Region. We combined estimated exposures with 2016 American Community Summary Census data, at the block group level, using spatial analysis to investigate whether exposures to these pollutants differ by race and ethnicity, age, income, education, and language proficiency. Based on these estimations, we assessed associated exposure risks to the impacted communities and used multivariable regression modeling to evaluate the relationship between average ammonia exposures from Duplin regional hog farms and the presence of vulnerable populations.

RESULTS

The average [± standard deviation  ( SD ) ] annual estimated concentration of NH 3 and H 2 S in the Duplin County Region is 1.75 ± 2.81   μ g / m 3 and 0.0087 ± 0.014   μ g / m 3 , respectively. The maximum average annual ambient concentrations are estimated at 54.27 ± 4.12   μ g / m 3 and 0.54 ± 0.041   μ g / m 3 for NH 3 and H 2 S , respectively. Our descriptive analysis reveals that people of low income, people of color, people with low educational attainment, and the linguistically isolated in the Duplin Region are disproportionately exposed to higher levels of pollutants than the average exposure for residents. Alternatively, our statistical results suggests that after adjusting for covariates, communities of color are associated with 1.70% (95% CI: - 3.79 , 0.44) lower NH 3 concentrations per 1-SD increase. One-standard deviation increases in the adults with low educational attainment and children < 19 years of age is associated with 1.26% (95% CI: - 0.77 , 3.33) and 1.20% (95% CI: - 0.62 , 3.05) higher NH 3 exposure per 1-SD increase, respectively.

DISCUSSION

Exposures to NH 3 and H 2 S differed by race and ethnicity, educational attainment, language proficiency, and socioeconomic status. The observed associations between exposure to CAFO-generated pollutants and sociodemographic indicators differed among demographics. The disproportionate distribution of hog facilities and resulting pollutant exposures among communities may have adverse environmental and human health impacts, raising environmental justice concerns. https://doi.org/10.1289/EHP11344.

Disparities in greenspace associated with sleep duration among adolescent children in Southern California

More than half of adolescent children do not get the recommended 8 hours of sleep necessary for optimal growth and development. In adults, several studies have evaluated effects of urban stressors including lack of greenspace, air pollution, noise, nighttime light, and psychosocial stress on sleep duration. Little is known about these effects in adolescents, however, it is known that these exposures vary by socioeconomic status (SES). We evaluated the association between several environmental exposures and sleep in adolescent children in Southern California.

Methods

In 2010, a total of 1476 Southern California Children's Health Study (CHS) participants in grades 9 and 10 (mean age, 13.4 years; SD, 0.6) completed a questionnaire including topics on sleep and psychosocial stress. Exposures to greenspace, artificial light at night (ALAN), nighttime noise, and air pollution were estimated at each child's residential address, and SES was characterized by maternal education. Odds ratios and 95% confidence intervals (95% CIs) for sleep outcomes were estimated by environmental exposure, adjusting for age, sex, race/ethnicity, home secondhand smoke, and SES.

Results

An interquartile range (IQR) increase in greenspace decreased the odds of not sleeping at least 8 hours (odds ratio [OR], 0.86 [95% CI, 0.71, 1.05]). This association was significantly protective in low SES participants (OR, 0.77 [95% CI, 0.60, 0.98]) but not for those with high SES (OR, 1.16 [95%CI, 0.80, 1.70]), interaction P = 0.03. Stress mediated 18.4% of the association among low SES participants.

Conclusions

Residing in urban neighborhoods of greater greenness was associated with improved sleep duration among children of low SES but not higher SES. These findings support the importance of widely reported disparities in exposure and access to greenspace in socioeconomically disadvantaged populations.

Impact of Global Climate Change on Pulmonary Health: Susceptible and Vulnerable Populations

As fossil fuel combustion continues to power the global economy, the rate of climate change is accelerating, causing severe respiratory health impacts and large disparities in the degree of human suffering. Hotter and drier climates lead to longer and more severe wildland fire seasons, impairing air quality around the globe. Hotter temperatures lead to higher amounts of ozone and particles, causing the exacerbation of chronic respiratory diseases and premature mortality. Longer pollen seasons and higher pollen concentrations provoke allergic airway diseases. In arid regions, accelerated land degradation and desertification are promoting dust pollution and impairing food production and nutritional content that are essential to respiratory health. Extreme weather events and flooding impede healthcare delivery and can lead to poor indoor air quality due to mold overgrowth. Climate and human activities that harm the environment and ecosystem may also affect the emergence and spread of viral infections, including severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), and associated morbidity and mortality exacerbated by air pollution. Children and elderly individuals are more susceptible to the adverse health effects of climate change. Geographical and socioeconomic circumstances, together with a decreased capacity to adapt, collectively increase vulnerability to the adverse effects of climate change. Successful mitigation of anthropogenic climate change is dependent on the commitment of energy-intensive nations to manage greenhouse gas emissions, as well as societal support and response to aggravating factors. In this review, we focus on the respiratory health impacts of global climate change, with an emphasis on susceptible and vulnerable populations and low- and middle-income countries.

Air pollution and associated health impact and economic loss embodied in inter-provincial electricity transfer in China

As the largest producer and consumer of coal in the world, China heavily relies on coal resources for thermal power generation. Owing to the unbalanced distribution of energy resources, electricity transfer among regions in China plays a key role in promoting economic growth and ensuring energy safety. However, little is known about air pollution and the related health impacts resulting from electricity transfer. This study assessed PM_2.5 pollution and related health and economic losses attributable to the inter-provincial electricity transfer in mainland China in 2016. The results show that a large amount of virtual air pollutant emissions were transferred from energy-abundant northern, western and central China to well-developed and populated eastern coastal regions. Correspondingly, the inter-provincial electricity transfer dramatically reduced the atmospheric levels of PM_2.5 and related health and economic losses in eastern and southern China, while increasing those in northern, western and central China. The health benefits attributable to inter-provincial electricity transfer were mainly found in Guangdong, Liaoning, Jiangsu and Shandong, whereas the extra health loss is concentrated in Hebei, Shanxi, Inner Mongolia, and Heilongjiang. Overall, the inter-provincial electricity transfer led to an extra increase of 3600 (95 % CI: 3200-4100) PM_2.5-related deaths and 345 (95 % CI: 294-389) million USD of economic loss in China in 2016. The results could assist air pollution mitigation strategies for the thermal power sector in China by strengthening the cooperation between suppliers and consumers of electricity.

Effect of Omega-3 Polyunsaturated Fatty Acids on Cardiovascular Outcomes in Patients with Diabetes: A Meta-analysis of Randomized Controlled Trials

The current guidelines recommend that people consume 2 or more servings of fat-rich fish per week to obtain enough omega-3 (ω-3) polyunsaturated fatty acids to prevent cardiovascular events. However, the cardiovascular benefits of ω-3 polyunsaturated fatty acids in patients with diabetes are unclear, and related large-scale trials have produced conflicting results. We aimed to perform a meta-analysis of all randomized controlled trials that attempted to assess the effects of ω-3 fatty acid supplementation on cardiovascular outcomes in patients with diabetes. In PubMed, EMBASE, and the Cochrane Library, we searched for data from all randomized controlled trials on ω-3 fatty acids and cardiovascular outcomes in patients with diabetes published before July 2022. Eight eligible studies involving 57,754 participants were ultimately included. Meta-analysis showed that ω-3 fatty acid supplementation reduces cardiovascular disease (CVD) risk in patients with diabetes (rate ration [RR] = 0.93; 95% confidence interval [CI]: 0.90, 0.97; P = 0.0009). Among them, eicosapentaenoic acid (EPA), but not EPA plus docosahexaenoic acid (DHA), significantly reduced the risk of CVD in patients with diabetes (EPA [RR = 0.81; 95% CI: 0.73, 0.90; P=0.0001]). This meta-analysis suggests that ω-3 fatty acid supplementation is an effective strategy to prevent CVD in patients with diabetes, but further well-designed, large-scale randomized controlled trials are necessary to evaluate the safety of ω-3 fatty acid supplementation, and its effect on atrial fibrillation. This study was registered with PROSPERO as CRD42022346302.

Structural racism, air pollution and the association with adverse birth outcomes in the United States: the value of examining intergenerational associations

Structurally racist policies and practices of the past are likely to be a driving factor in current day differences in exposure to air pollution and may contribute to observed racial and ethnic disparities in adverse birth outcomes in the United States (U.S.). Non-Hispanic Black women in the U.S. experience poorer health outcomes during pregnancy and throughout the life course compared to non-Hispanic White women. This disparity holds even among non-Hispanic Black women with higher socioeconomic status. Reasons for this finding remain unclear, but long-term environmental exposure, either historical exposure or both historical and ongoing exposure, may contribute. Structural racism likely contributes to differences in social and environmental exposures by race in the U.S. context, and these differences can affect health and wellbeing across multiple generations. In this paper, we briefly review current knowledge and recommendations on the study of race and structural racism in environmental epidemiology, specifically focused on air pollution. We describe a conceptual framework and opportunities to use existing historical data from multiple sources to evaluate multi-generational influences of air pollution and structurally racist policies on birth and other relevant health outcomes. Increased analysis of this kind of data is critical for our understanding of structural racism's impact on multiple factors, including environmental exposures and adverse health outcomes, and identifying how past policies can have enduring legacies in shaping health and well-being in the present day. The intended purpose of this manuscript is to provide an overview of the widespread reach of structural racism, its potential association with health disparities and a comprehensive approach in environmental health research that may be required to study and address these problems in the U.S. The collaborative and methodological approaches we highlight have the potential to identify modifiable factors that can lead to effective interventions for health equity.