Accuracy of self-reported distance to nearest unconventional oil and gas well in Pennsylvania, Ohio, and West Virginia residents and implications for exposure assessment.

Self-reported distances to industrial sources have been used in epidemiology as proxies for exposure to environmental hazards and indicators of awareness and perception of sources. Unconventional oil and gas development (UOG) emits pollutants and has been associated with adverse health outcomes. We compared self-reported distance to the nearest UOG well to the geographic information system-calculated distance for 303 Pennsylvania, Ohio, and West Virginia residents using Cohen's Weighted Kappa. Agreement was low (Kappa = 0.18), and self-reports by Ohioans (39% accuracy) were more accurate than West Virginians (22%) or Pennsylvanians (13%, both p < 0.05). Of the demographic characteristics studied, only educational attainment was related to reporting accuracy; residents with 12-16 years of education were more accurate (31.3% of group) than those with <12 or >16 years (both 16.7%). Understanding differences between objective and subjective measures of UOG proximity could inform studies of perceived exposures or risks and may also be relevant to adverse health effects. IMPACT: We compared objective and self-reported measures of distance to the nearest UOG well for 303 Appalachian Basin residents. We found that residents' self-reported distance to the nearest UOG well had limited agreement with the true calculated distance category. Our results can be used to inform the collection and contextualize the use of self-reported data in communities exposed to UOGD. Self-reported metrics can be used in conjunction with objective assessments and can be informative regarding how potentially exposed populations perceive environmental exposures or risks and could provide insights into awareness of distance-related policies, such as setbacks.

Predictors of early life residential mobility in urban and rural Pennsylvania children with acute lymphoblastic leukemia and implications for environmental exposure assessment.

BACKGROUND: Residential mobility can introduce exposure misclassification in pediatric epidemiology studies using birth address only. OBJECTIVE: We examined whether residential mobility varies by sociodemographic factors and urbanicity/rurality among children with cancer. METHODS: Our study included 400 children born in Pennsylvania during 2002-2015 and diagnosed with leukemia at ages 2-7 years. Addresses were obtained from state registries at birth and diagnosis. We considered three aspects of mobility between birth and diagnosis: whether a child moved, whether a mover changed census tract, and distance moved. We evaluated predictors of these aspects in urban- and rural-born children using chi-square, t-tests, and regression analyses. RESULTS: Overall, 58% of children moved between birth and diagnosis; suburban/rural-born children were more likely to move than urban-born children (67% versus 57%). The mean distance moved was 16.7 km in suburban/rural-born and 14.8 km in urban-born movers. In urban-born children, moving between birth and diagnosis was associated with race, education, participation in the Nutrition Program for Women, Infants and Children (WIC), and census tract-level income (all χ2 p < 0.01). Urban-born movers tended to be born in a census tract with a higher Social Vulnerability Index than non-movers (t-test p < 0.01). No factors were statistically significantly associated with any of the residential mobility metrics in suburban/rural-born children, although the sample size was small. IMPACT STATEMENT: In this study of a vulnerable population of children with cancer, we found that rural-born children were more likely to move than urban-born children, however, the frequency of movers changing census tracts was equivalent. Mobility in urban-born children, but not rural-born, was associated with several social factors, although the sample size for rural-born children was small. Mobility could be an important source of misclassification depending on the spatial heterogeneity and resolution of the exposure data and whether the social factors are related to exposures or health outcomes. Our results highlight the importance of considering differences in mobility between urban and rural populations in spatial research.

An environmental justice analysis of air pollution in India.

Due to the lack of timely data on socioeconomic factors (SES), little research has evaluated if socially disadvantaged populations are disproportionately exposed to higher PM2.5 concentrations in India. We fill this gap by creating a rich dataset of SES parameters for 28,081 clusters (villages in rural India and census-blocks in urban India) from the National Family and Health Survey (NFHS-4) using a precision-weighted methodology that accounts for survey-design. We then evaluated associations between total, anthropogenic and source-specific PM2.5 exposures and SES variables using fully-adjusted multilevel models. We observed that SES factors such as caste, religion, poverty, education, and access to various household amenities are important risk factors for PM2.5 exposures. For example, we noted that a unit standard deviation increase in the cluster-prevalence of Scheduled Caste and Other Backward Class households was significantly associated with an increase in total-PM2.5 levels corresponding to 0.127 µg/m3 (95% CI 0.062 µg/m3, 0.192 µg/m3) and 0.199 µg/m3 (95% CI 0.116 µg/m3, 0.283 µg/m3, respectively. We noted substantial differences when evaluating such associations in urban/rural locations, and when considering source-specific PM2.5 exposures, pointing to the need for the conceptualization of a nuanced EJ framework for India that can account for these empirical differences. We also evaluated emerging axes of inequality in India, by reporting associations between recent changes in PM2.5 levels and different SES parameters.

Global population exposure to landscape fire air pollution from 2000 to 2019.

Wildfires are thought to be increasing in severity and frequency as a result of climate change1-5. Air pollution from landscape fires can negatively affect human health4-6, but human exposure to landscape fire-sourced (LFS) air pollution has not been well characterized at the global scale7-23. Here, we estimate global daily LFS outdoor fine particulate matter (PM2.5) and surface ozone concentrations at 0.25° × 0.25° resolution during the period 2000-2019 with the help of machine learning and chemical transport models. We found that overall population-weighted average LFS PM2.5 and ozone concentrations were 2.5 µg m-3 (6.1% of all-source PM2.5) and 3.2 µg m-3 (3.6% of all-source ozone), respectively, in 2010-2019, with a slight increase for PM2.5, but not for ozone, compared with 2000-2009. Central Africa, Southeast Asia, South America and Siberia experienced the highest LFS PM2.5 and ozone concentrations. The concentrations of LFS PM2.5 and ozone were about four times higher in low-income countries than in high-income countries. During the period 2010-2019, 2.18 billion people were exposed to at least 1 day of substantial LFS air pollution per year, with each person in the world having, on average, 9.9 days of exposure per year. These two metrics increased by 6.8% and 2.1%, respectively, compared with 2000-2009. Overall, we find that the global population is increasingly exposed to LFS air pollution, with socioeconomic disparities.

Concentrated animal feeding operations (CAFOs) in relation to environmental justice related variables in Wisconsin, United States.

BACKGROUND: The growth of concentrated animal feeding operations (CAFOs) has caused significant environmental detriments and raised concerns regarding environmental justice with CAFOs exposure. OBJECTIVE: This study examined environmental disparities in exposure to CAFOs with several environmental justice related variables and considered exposure intensity. METHODS: We obtained data on permitted CAFOs (July 2021) from the Wisconsin Department of Natural Resources. We used Census tract level variables from the 2010 Census to evaluate environmental disparities by environmental justice related variables (i.e., percentages of Non-Hispanic White, Non-Hispanic Black, or Hispanic; percentage living below the poverty level; median annual household income; income inequality (Gini index); percentage with education less than high school diploma; racial isolation (RI) for Non-Hispanic Black; and educational isolation (EI) for population without a college degree). We assessed exposure to CAFOs as the sum of animal units (AUs) within each Census tract and investigated exposure disparities by comparing distributions of environmental justice related variables based on CAFO status (i.e., never, expired, or current) and Census tract-level CAFOs exposure intensity categories (i.e., from low exposure (quartile 1) to high exposure (quartile 4)). RESULTS: CAFOs in Wisconsin were generally located in areas with lower percentages of racial minority persons and high SES communities; however, within the areas with current CAFO exposure, areas with high CAFOs exposure intensity had higher percentages of non-Hispanic Black and Hispanic, and lower percentages of non-Hispanic White populations compared to areas with low CAFOs exposure. IMPACT STATEMENT: This study compared distributions of CAFO exposure and multiple environmental justice related variables and considered exposure intensity based on animal units for CAFOs exposure metric. Although CAFOs in Wisconsin were generally located in areas with lower percentages of racial/ethnic minority subpopulations and high SES communities, we found complex disparities with higher exposure for disadvantaged communities within areas with CAFOs. This work adds to the existing evidence that some populations such as racial/ethnic minority populations may face disproportionate burdens from CAFOs.

Exposures to ambient particulate matter are associated with reduced adult earnings potential.

The societal costs of air pollution have historically been measured in terms of premature deaths (including the corresponding values of statistical lives lost), disability-adjusted life years, and medical costs. Emerging research, however, demonstrated potential impacts of air pollution on human capital formation. Extended contact with pollutants such as airborne particulate matter among young persons whose biological systems are still developing can result in pulmonary, neurobehavioral, and birth complications, hindering academic performance as well as skills and knowledge acquisition. Using a dataset that tracks 2014-2015 incomes for 96.2% of Americans born between 1979 and 1983, we assessed the association between childhood exposure to fine particulate matter (PM2.5) and adult earnings outcomes across U.S. Census tracts. After accounting for pertinent economic covariates and regional random effects, our regression models indicate that early-life exposure to PM2.5 is associated with lower predicted income percentiles by mid-adulthood; all else equal, children raised in high pollution tracts (at the 75th percentile of PM2.5) are estimated to have approximately a 0.51 decrease in income percentile relative to children raised in low pollution tracts (at the 25th percentile of PM2.5). For a person earning the median income, this difference corresponds to a $436 lower annual income (in 2015 USD). We estimate that 2014-2015 earnings for the 1978-1983 birth cohort would have been ∼$7.18 billion higher had their childhood exposure met U.S. air quality standards for PM2.5. Stratified models show that the relationship between PM2.5 and diminished earnings is more pronounced for low-income children and for children living in rural environments. These findings raise concerns about long-term environmental and economic justice for children living in areas with poor air quality where air pollution could act as a barrier to intergenerational class equity.

Air Pollution and Acute Kidney Injury in the U.S. Medicare Population: A Longitudinal Cohort Study.

BACKGROUND: Recent studies have reported the association between air pollution exposure and reduced kidney function. However, it is unclear whether air pollution is associated with an increased risk of acute kidney injury (AKI). OBJECTIVES: To address this gap in knowledge, we investigated the effect estimates of long-term exposures to fine particulate matter [PM ≤2.5µm in aerodynamic diameter (PM2.5)], nitrogen dioxide (NO2), and ozone (O3) on the risk of first hospital admission for AKI using nationwide Medicare data. METHODS: This nationwide population-based longitudinal cohort study included 61,300,754 beneficiaries enrolled in Medicare Part A fee-for-service (FFS) who were ≥65 years of age and resided in the continental United States from the years 2000 through 2016. We applied Cox-equivalent Poisson models to estimate the association between air pollution and first hospital admission for AKI. RESULTS: Exposure to PM2.5, NO2, and O3 was associated with increased risk for first hospital admission for AKI, with hazard ratios (HRs) of 1.17 (95% CI: 1.16, 1.19) for a 5-µg/m3 increase in PM2.5, 1.12 (95% CI: 1.11, 1.13) for a 10-ppb increase in NO2, and 1.03 (95% CI: 1.02, 1.04) for a 10-ppb increase in summer-period O3 (June to September). The associations persisted at annual exposures lower than the current National Ambient Air Quality Standard. DISCUSSION: This study found an association between exposures to air pollution and the risk of the first hospital admission with AKI, and this association persisted even at low concentrations of air pollution. Our findings provide beneficial implications for public health policies and air pollution guidelines to alleviate health care expenditures and the disease burden attributable to AKI. https://doi.org/10.1289/EHP10729.

Hospital admission risks and excess costs for neurological symptoms attributable to long-term exposure to fine particulate matter in New York State, USA.

BACKGROUND: Although emerging evidence suggests that PM2.5 is linked to neurological symptoms (NSs) via neuroinflammation, relevant studies are scarce. This study aimed to investigate the risks and excess costs of hospital admission for five NSs-fatigue, headache, dizziness, convulsion, and paralysis-attributable to long-term exposure to PM2.5 in New York State, USA. METHODS: We analyzed the New York Statewide Planning and Research Cooperative System (SPARCS) from 2010 to 2016. A Bayesian hierarchical model with integrated nested Laplace approximations was performed to estimate the risks and excess costs of hospital admission for NSs due to long-term exposure to PM2.5 at the county level. RESULTS: A 1 µg/m3 increase in lag 0-1 years PM2.5 was associated with an increased risk of headache and convulsion by 1.06 (1.01, 1.11) and 1.04 (1.01, 1.06), respectively. The excess hospital admission cost for five NSs attributable to lag 0-1 years PM2.5 above the new World Health Organization guideline (annual standard: 5 µg/m3) was $200.24 (95% CI: 6.00, 376.96) million during 2011-2016, recording the highest for convulsion ($153.73 [95% CI: 63.61, 244.19] million). CONCLUSIONS: This study provides quantitative estimates of risks and excess costs for NSs attributable to long-term PM2.5 and suggests that policies that reduce long-term PM2.5 concentration in accordance with the new WHO air quality guidelines can yield substantial health and economic benefits related to NSs in the New York State population.

Associations between greenness and kidney disease in Massachusetts: The US Medicare longitudinal cohort study.

BACKGROUND: Recent studies have identified the association of environmental stressors with reduced kidney function and the development of kidney disease. While residential greenness has been linked to many health benefits, the association between residential greenness and the development of kidney disease is not clear. We aimed to investigate the association between residential greenness and the development of kidney disease. METHODS: We performed a longitudinal population-based cohort study including all fee-for-service Medicare Part A beneficiaries (aged 65 years or older) in Massachusetts (2000-2016). We assessed greenness with the annual average Enhanced Vegetation Index (EVI) based on residential ZIP codes of beneficiaries. We applied Cox-equivalent Poisson models to estimate the association between EVI and first hospital admission for total kidney disease, chronic kidney disease (CKD), and acute kidney injury (AKI), separately. RESULTS: Data for 1,462,949 beneficiaries who resided in a total of 644 ZIP codes were analyzed. The total person-years of follow-up for total kidney disease, CKD, and AKI were 9.8, 10.9, and 10.8 million person-years, respectively. For a 0.1 increase in annual EVI, the hazard ratios (HRs) were 0.95 (95% CI: 0.93 to 0.97) for the first hospital admission for total kidney disease, and the association was more prominent for AKI (HR: 0.94 with 95% CI: 0.92 to 0.97) than CKD (HR: 0.98 with 95% CI: 0.95-1.01]). The estimated effects of EVI on kidney disease were generally more evident in White beneficiaries and those residing in metropolitan areas compared to the overall population. CONCLUSIONS: This study found that higher levels of annual residential greenness were associated with a lower risk of the first hospital admission for kidney diseases. Results are consistent with the hypothesis that higher residential greenness benefits kidney patients.

Assessing community-level exposure to social vulnerability and isolation: spatial patterning and urban-rural differences.

BACKGROUND: Environmental health disparity research involves the use of metrics to assess exposure to community-level vulnerabilities or inequities. While numerous vulnerability indices have been developed, there is no agreement on standardization or appropriate use, they have largely been applied in urban areas, and their interpretation and utility likely vary across different geographies. OBJECTIVE: We evaluated the spatial distribution, variability, and relationships among different metrics of social vulnerability and isolation across urban and rural settings to inform interpretation and selection of metrics for environmental disparity research. METHODS: For all census tracts in North Carolina, we conducted a principal components analysis using 23 socioeconomic/demographic variables from the 2010 United States Census and American Community Survey. We calculated or obtained the neighborhood deprivation index (NDI), residential racial isolation index (RI), educational isolation index (EI), Gini coefficient, and social vulnerability index (SVI). Statistical analyses included Moran's I for spatial clustering, t-tests for urban-rural differences, Pearson correlation coefficients, and changes in ranking of tracts across metrics. RESULTS: Social vulnerability metrics exhibited clear spatial patterning (Moran's I ≥ 0.30, p < 0.01). Greater educational isolation and more intense neighborhood deprivation was observed in rural areas and greater racial isolation in urban areas. Single-domain metrics were not highly correlated with each other (rho ≤ 0.36), while composite metrics (i.e., NDI, SVI, principal components analysis) were highly correlated (rho > 0.80). Composite metrics were more highly correlated with the racial isolation metric in urban (rho: 0.54-0.64) versus rural tracts (rho: 0.36-0.48). Census tract rankings changed considerably based on which metric was being applied. SIGNIFICANCE: High correlations between composite metrics within urban and rural tracts suggests they could be used interchangeably; single domain metrics cannot. Composite metrics capture different facets of vulnerabilities in urban and rural settings, and these complexities should be examined by researchers applying metrics to areas of diverse urban and rural forms.

Investigation on urban greenspace in relation to sociodemographic factors and health inequity based on different greenspace metrics in 3 US urban communities.

BACKGROUND: Study results are inconclusive regarding how access to greenspace differs by sociodemographic status potentially due to lack of consideration of varying dimensions of greenspace. OBJECTIVE: We investigated how provision of greenspace by sociodemographic status varies by greenspace metrics reflecting coverage and accessibility of greenspace. METHODS: We used vegetation levels measured by Enhanced Vegetation Index (EVI), percent of greenspace, percent tree cover, percent tree cover along walkable roads, and percent of people living ≤500 m of a park entrance (park accessibility). We considered data for 2008-2013 in Census block groups in 3 US regions: New Haven, Connecticut; Baltimore, Maryland; and Durham, North Carolina. We examined geographical distribution of greenspace metrics and their associations with indicators of income, education, linguistic isolation, race/ethnicity, and age. We used logistic regression to examine associations between these greenspace metrics and age-standardized mortality controlling for sociodemographic indicators. RESULTS: Which region had the highest greenspace depended on the greenspace metric used. An interquartile range (33.6%) increase in low-income persons was associated with a 6.2% (95% CI: 3.1, 9.3) increase in park accessibility, whereas it was associated with 0.03 (95% CI: -0.035, -0.025) to 7.3% (95% CI: -8.7, -5.9) decreases in other greenspace metrics. A 15.5% increase in the lower-education population was associated with a 2.1% increase (95% CI: -0.3%, 4.6%) in park accessibility but decreases with other greenspace metrics (0.02 to 5.0%). These results were consistent across the 3 study areas. The odds of mortality rate more than the 75th percentile rate were inversely associated with all greenspace metrics except for annual average EVI (OR 1.27, 95% CI: 0.43, 3.79) and park accessibility (OR 1.40, 95% CI: 0.52, 3.75). SIGNIFICANCE: Environmental justice concerns regarding greenspace differ by the form of natural resources, and pathways of health benefits can differ by form of greenspace and socioeconomic status within communities. IMPACT STATEMENT: Comparisons of exposure to greenspace between different greenspace metrics should be incorporated in decision-making within local contexts.

Effect modification of greenness on the association between heat and mortality: A multi-city multi-country study.

BACKGROUND: Identifying how greenspace impacts the temperature-mortality relationship in urban environments is crucial, especially given climate change and rapid urbanization. However, the effect modification of greenspace on heat-related mortality has been typically focused on a localized area or single country. This study examined the heat-mortality relationship among different greenspace levels in a global setting. METHODS: We collected daily ambient temperature and mortality data for 452 locations in 24 countries and used Enhanced Vegetation Index (EVI) as the greenspace measurement. We used distributed lag non-linear model to estimate the heat-mortality relationship in each city and the estimates were pooled adjusting for city-specific average temperature, city-specific temperature range, city-specific population density, and gross domestic product (GDP). The effect modification of greenspace was evaluated by comparing the heat-related mortality risk for different greenspace groups (low, medium, and high), which were divided into terciles among 452 locations. FINDINGS: Cities with high greenspace value had the lowest heat-mortality relative risk of 1·19 (95% CI: 1·13, 1·25), while the heat-related relative risk was 1·46 (95% CI: 1·31, 1·62) for cities with low greenspace when comparing the 99th temperature and the minimum mortality temperature. A 20% increase of greenspace is associated with a 9·02% (95% CI: 8·88, 9·16) decrease in the heat-related attributable fraction, and if this association is causal (which is not within the scope of this study to assess), such a reduction could save approximately 933 excess deaths per year in 24 countries. INTERPRETATION: Our findings can inform communities on the potential health benefits of greenspaces in the urban environment and mitigation measures regarding the impacts of climate change. FUNDING: This publication was developed under Assistance Agreement No. RD83587101 awarded by the U.S. Environmental Protection Agency to Yale University. It has not been formally reviewed by EPA. The views expressed in this document are solely those of the authors and do not necessarily reflect those of the Agency. EPA does not endorse any products or commercial services mentioned in this publication. Research reported in this publication was also supported by the National Institute on Minority Health and Health Disparities of the National Institutes of Health under Award Number R01MD012769. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. Also, this work has been supported by the National Research Foundation of Korea (2021R1A6A3A03038675), Medical Research Council-UK (MR/V034162/1 and MR/R013349/1), Natural Environment Research Council UK (Grant ID: NE/R009384/1), Academy of Finland (Grant ID: 310372), European Union's Horizon 2020 Project Exhaustion (Grant ID: 820655 and 874990), Czech Science Foundation (22-24920S), Emory University's NIEHS-funded HERCULES Center (Grant ID: P30ES019776), and Grant CEX2018-000794-S funded by MCIN/AEI/ 10.13039/501100011033 The funders had no role in the design, data collection, analysis, interpretation of results, manuscript writing, or decision to publication.

The Intersection of Immigrant and Environmental Health: A Scoping Review of Observational Population Exposure and Epidemiologic Studies.

BACKGROUND: Transnational immigration has increased since the 1950s. In countries such as the United States, immigrants now account for >15% of the population. Although differences in health between immigrants and nonimmigrants are well documented, it is unclear how environmental exposures contribute to these disparities. OBJECTIVES: We summarized current knowledge comparing immigrants' and nonimmigrants' exposure to and health effects of environmental exposures. METHODS: We conducted a title and abstract review on articles identified through PubMed and selected those that assessed environmental exposures or health effects separately for immigrants and nonimmigrants. After a full text review, we extracted the main findings from eligible studies and categorized each article as exposure-focused, health-focused, or both. We also noted each study's exposure of interest, study location, exposure and statistical methods, immigrant and comparison groups, and the intersecting socioeconomic characteristics controlled for. RESULTS: We conducted a title and abstract review on 3,705 articles, a full text review on 84, and extracted findings from 50 studies. There were 43 studies that investigated exposure (e.g., metals, organic compounds, fine particulate matter, hazardous air pollutants) disparities, but only 12 studies that assessed health disparities (e.g., mortality, select morbidities). Multiple studies reported higher exposures in immigrants compared with nonimmigrants. Among immigrants, studies sometimes observed exposure disparities by country of origin and time since immigration. Of the 50 studies, 43 were conducted in North America. DISCUSSION: The environmental health of immigrants remains an understudied area, especially outside of North America. Although most identified studies explored potential exposure disparities, few investigated subsequent differences in health effects. Future research should investigate environmental health disparities of immigrants, especially outside North America. Additional research gaps include the role of immigrants' country of origin and time since immigration, as well as the combined effects of immigrant status with intersecting socioeconomic characteristics, such as race/ethnicity, income, and education attainment. https://doi.org/10.1289/EHP9855.

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.

Queering Environmental Justice: Unequal Environmental Health Burden on the LGBTQ+ Community.

The LGBTQ+ (lesbian, gay, bisexual, transgender/-sexual, queer or questioning, intersex, asexual, and all subsects) population has been the target of federal and state discriminatory policies leading to high levels of institutional discrimination in the housing, employment, and health sectors. Social determinants of health such as housing conditions, economic opportunities, and access to health care may negatively and disproportionately affect the LGBTQ+ population and reduce their capacity to respond to environmental harm (e.g., obtaining necessary medical care). Social determinants of health have been shown to be associated with unequal harmful environmental exposure, primarily along lines of race/ethnicity and socioeconomic status. However, chronic diseases, such as respiratory diseases, cardiovascular disease, and cancer, associated with environmental exposure have been shown to occur in higher rates in the LGBTQ+ population than in the cisgender, heterosexual population. We explore how environmental exposures may disproportionately affect the LGBTQ+ population through examples of environmental exposures, health risks that have been linked to environmental exposures, and social institutions that could affect resilience to environmental stressors for this population. We provide recommendations for policymakers, public health officials, and researchers. (Am J Public Health. 2022;112(1):79-87. https://doi.org/10.2105/AJPH.2021.306406).

Do temporal trends of associations between short-term exposure to fine particulate matter (PM2.5) and risk of hospitalizations differ by sub-populations and urbanicity-a study of 968 U.S. counties and the Medicare population.

While associations between short-term exposure to fine particulate matter (PM2.5) and risk of hospitalization are well documented and evidence suggests that such associations change over time, it is unclear whether these temporal changes exist in understudied less-urban areas or differ by sub-population. We analyzed daily time-series data of 968 continental U.S. counties for 2000-2016, with cause-specific hospitalization from Medicare claims and population-weighted PM2.5 concentrations originally estimated at 1km × 1 km from a hybrid model. Circulatory and respiratory hospitalizations were categorized based on primary diagnosis codes at discharge. Using modified Bayesian hierarchical modelling, we evaluated the temporal trend in association between PM2.5 and hospitalizations and whether disparities in this trend exist across individual-level characteristics (e.g., sex, age, race, and Medicaid eligibility as a proxy for socio-economic status) and urbanicity. Urbanicity was categorized into three levels by county-specific percentage of urban population based on urban rural delineation from the U.S. Census. In this cohort with understudied less-urban areas without regulatory monitors, we still found positive association between circulatory and respiratory hospitalization and short-term exposure to PM2.5, with higher effect estimates towards the end of study period. Consistent with current literature, we identified significant disparity in associations by race, socioeconomic status and urbanicity. We found that the percentage change in circulatory hospitalization rate per 10 µg/m3 increase in PM2.5 was higher in the 2008-2016 time period compared to the 2000-2007 period by 0.33% (95% posterior credible interval 0.22, 0.44%), 0.52% (0.33, 0.69%), and 0.67% (0.53, 0.83%) for low, medium and high tertiles of urban areas, respectively. We also observed significant differences in temporal trends of associations across socioeconomic status, sex, and age, indicating a possible widening in disparity of PM2.5-related health burden. This study raises the importance of considering environmental justice issues in PM2.5-related health impacts with respect to how associations may change over time.

Temporal variation in association between short-term exposure to fine particulate matter and hospitalisations in older adults in the USA: a long-term time-series analysis of the US Medicare dataset.

BACKGROUND: Short-term exposure to fine particulate matter (PM2·5) is associated with increased risk of hospital admissions and mortality, and health risks differ by the chemical composition of PM2·5. Policies to control PM2·5 could change its chemical composition and total mass concentration, leading to change in the subsequent health impact. However, there is little ence on whether associations between PM2·5 and health exhibit temporal variation. We investigated whether risks of hospitalisations from short-term exposure to PM2·5 varied over time in the USA. METHODS: We did a time-series analysis using a national dataset comprising daily circulatory and respiratory hospitalisation rates of Medicare beneficiaries (age ≥65 years) and PM2·5 in 173 US counties from 1999 to 2016. We fitted modified quasi-Poisson models to estimate temporal trends of associations within a county, and pooled county-level estimates using Bayesian hierarchical modelling to generate an overall estimate. FINDINGS: The study included 10 559 654 circulatory and 3 027 281 respiratory hospitalisations. We identified changes in the national average association between previous-day PM2·5 and respiratory hospitalisation over time, with a U-shape that is robust under stratification, linear, and non-linear models. The change in risk of respiratory hospitalisation per 10 µg/m3 increase in previous-day PM2·5 decreased from 0·75% (95% posterior credible interval 0·05 to 1·46) in 1999 to -0·28% (-0·79 to 0·23) in 2008, and then increased to 1·44% (0·00 to 2·91) in 2016. No statistically significant temporal change was observed for associations between same-day PM2·5 and circulatory hospitalisation. INTERPRETATION: Hospitalisation risk from PM2·5 changes over time and has increased over the past 7 years in study, especially in northeastern USA. The temporal trend differs by cause of hospitalisation. This study emphasises the necessity of evaluating temporal heterogeneity in health impacts of PM2·5 and suggests caution in applying association estimates to a different time period. FUNDING: US Environmental Protection Agency and Yale Institute for Biospheric Studies.

Temporal changes in associations between high temperature and hospitalizations by greenspace: Analysis in the Medicare population in 40 U.S. northeast counties.

Although research indicates health and well-being benefits of greenspace, little is known regarding how greenspace may influence adaptation to health risks from heat, particularly how these risks change over time. Using daily hospitalization rates of Medicare beneficiaries ≥65 years for 2000-2016 in 40 U.S. Northeastern urban counties, we assessed how temperature-related hospitalizations from cardiovascular causes (CVD) and heat stroke (HS) changed over time. We analyzed effect modification of those temporal changes by Enhanced Vegetation Index (EVI), approximating greenspace. We used a two-stage analysis including a generalized additive model and meta-analysis. Results showed that relative risk (RR) (per 1 °C increase in lag0-3 temperature) for temperature-HS hospitalization was higher in counties with the lowest quartile EVI (RR = 2.7, 95% CI: 2.0, 3.4) compared to counties with the highest quartile EVI (RR = 0.40, 95% CI: 0.14, 1.13) in the early part of the study period (2000-2004). RR of HS decreased to 0.88 (95% CI: 0.31, 2.53) in 2013-2016 in counties with the lowest quartile EVI. RR for HS changed over time in counties in the highest quartile EVI, with RRs of 0.4 (95% CI: -0.7, 1.4) in 2000-2004 and 2.4 (95% CI: 1.6, 3.2) in 2013-2016. Findings suggest that adaptation to heat-health associations vary by greenness. Greenspace may help lower risks from heat but such health risks warrant continuous local efforts such as heat-health plans.

Community concern and government response: Identifying socio-economic and demographic predictors of oil and gas complaints and drinking water impairments in Pennsylvania.

Oil and gas development has led to environmental hazards and community concerns, particularly in relation to water supply issues. Filing complaints with state agencies enables citizens to register concerns and seek investigations. We evaluated associations between county-level socio-economic and demographic factors, oil and gas drilling, and three outcomes in Pennsylvania between 2004-2016: number of oil and gas complaints filed, and both the number and proportion of state investigations of water supply complaints yielding a confirmed water supply impairment (i.e., "positive determination"). We used hierarchical Bayesian Poisson and binomial regression analyses. From 2004-2016, 9,404 oil and gas-related complaints were filed, of which 4,099 were water supply complaints. Of those, 3,906 received investigations, and 215 yielded positive determinations. We observed a 47% increase in complaints filed per $10,000 increase in annual median household income (MHI) (Rate Ratio [RR]: 1.47, 95% credible interval [CI]: 1.09-1.96) and an 18% increase per 1% increase in educational attainment (RR: 1.18, 95% CI: 1.11-1.26). While the number of complaints filed did not vary by race/ethnicity, the odds of a complaint yielding a positive determination were 0.81 times lower in counties with a higher proportion of marginalized populations (Odds Ratio [OR]: 0.81 per 1% increase in percent Black, Asian, and Native American populations combined, 95% CI: 0.64-0.99). The odds of positive determinations were also lower in areas with higher income (OR per $10,000 increase in MHI: 0.35, 95% CI: 0.09-0.96). Our results suggest these relationships are complex and may indicate potential environmental and procedural inequities, warranting further investigation.

Temporal transition of racial/ethnic disparities in COVID-19 outcomes in 3108 counties of the United States: Three phases from January to December 2020.

Early studies reported higher risk of COVID-19 outcomes for racial/ethnic minorities in the early phase of the pandemic in the United States. While the initial surge of COVID-19 was concentrated in some areas, COVID-19 became pervasive across the entire continent with high impacts in the northern region and central region in the end of 2020. With this geographical transition, we aim to investigate patterns of these racial/ethnic disparities over time. We assessed associations of percentage of race/ethnic minorities and racial segregation indexes with COVID-19 case and mortality rates in 3108 counties of the continental United States during the pandemic's early phase, second, and third phase (January 21-June 15, June 16-August 31, and September 1-December 18, 2020, respectively). We adjusted for population density, age, and sex. We tested whether time-varying associations were consistent across climate regions and explained by socioeconomic variables. In the early phase, counties with higher percentage of Black/African Americans and higher Black-White segregation had higher COVID-19 case and mortality rates. These associations decreased over time and reversed in the third phase. Associations between Hispanic and COVID-19 outcomes were positive in all periods, but more so early in the pandemic. Higher COVID-19 case rates for counties with higher non-Hispanic White population emerged in the third phase. These trends were similar across climate regions, and socioeconomic variables did not explain these trends. In summary, county-level racial/ethnic disparities of COVID-19 are not stationary but change over the course of the pandemic, suggesting complex social, cultural, and political influences.