Assessment of sociodemographic and geographic disparities in cancer risk from air toxics in South Carolina

Inequalities in Environmental Cancer Risk and Carcinogen Exposures: A Scoping Review

Background: Cancer is the leading cause of death in Canada and a major cause of death worldwide. Environmental exposure to carcinogens and environments that may relate to health behaviors are important to examine as they can be modified to lower cancer risks. Built environments include aspects such as transit infrastructure, greenspace, food and tobacco environments, or land use, which may impact how people move, exercise, eat, and live. While environments may play a role in overall cancer risk, exposure to carcinogens or healthier environments is not equitably spread across space. Exposures to carcinogens commonly concentrate among socially and/or economically disadvantaged populations. While many studies have examined inequalities in exposure or cancer risk, this has commonly been for one exposure. Methods: This scoping review collected and synthesized research that examines inequities in carcinogenic environments and exposures. Results: This scoping review found that neighborhoods with higher proportions of low-income residents, racialized people, or same-sex couples had higher exposures to carcinogens and environments that may influence cancer risk. There are currently four main themes in research studying inequitable exposures: air pollution and hazardous substances, tobacco access, food access, and other aspects of the built environment, with most research still focusing on air pollution. Conclusions: More work is needed to understand how exposures to these four areas intersect with other factors to reduce inequities in exposures to support longer-term goals toward cancer prevention.

Geographic and social economic disparities in the risk of exposure to ambient air respiratory toxicants at Oklahoma licensed early care and education facilities

BACKGROUND

Early life exposures to hazardous air pollutants has been associated with adverse asthma-related outcomes. Neighborhood-level social and economic factors play an essential role in the distribution of hazardous air pollutants and children spend a substantial amount of time at early care and education (ECE) facilities. While the indoor air quality of these facilities has been described, particularly for criteria air pollutants such as volatile organic compounds and particulate matter, little is known about the ambient air quality of ECE facilities.

OBJECTIVES

We conducted a cross-sectional study to estimate the ambient air quality of Oklahoma licensed ECE facilities and to explore associations between ambient air quality and select geographic predictors.

METHODS

We estimated ambient air quality using the total respiratory hazard quotient from the National Air Toxics Assessment according to the geographical location of licensed Oklahoma ECE facilities (N = 3184). We then determined whether urban and rural ECE facilities' air respiratory toxicant exposure risk differed by ECE facilities' neighborhood-level social and economic inequities including: 1) racial-ethnic minority community, 2) neighborhood socioeconomic status, and 3) residential segregation.

RESULTS

Urban ECE facilities in Hispanic segregated counties were five times more likely to be at risk of high air respiratory exposure, adjusted for integrated urban counties (p < 0.0001, 95% CI [3.824, 7.699]). Rural ECE facilities in African American segregated counties were nine times more likely to be at risk of high air respiratory toxicant exposure, adjusted for integrated rural counties (p < 0.0001, 95% CI [5.641, 15.928]).

CONCLUSION

We found geographically and socially disparate patterns of higher exposures to ambient air respiratory toxicants at Oklahoma ECE facilities. Safer siting policies and interventions are needed to mitigate air respiratory toxicant exposures, which may help to reduce asthma control disparities and improve respiratory health outcomes in Oklahoma ECE facilities.

Carcinogenic air pollution along the United States' southern border: Neighborhood inequities in risk

Air pollution poses serious and socially inequitable risks to public health. Social disparities are marked along the US-Mexico border, yet prior research has not assessed inequities in air pollution exposure across the entire US-side of the border region. We apply an intersectional approach to examine contextually relevant sociodemographic variables, including (1) Hispanic/Latinx ethnicity by race and (2) nativity (US vs. Foreign) by citizenship, and cancer risks attributable to air pollution exposures. We pair data from the 2012-2016 American Community Survey with 2014 National Air Toxics Assessment estimates of carcinogenic risks from all sources of hazardous air pollutants at the census tract level (n = 1448) and use a series of generalized estimating equations to assess inequities in risk. Increased concentrations of renter-occupants, Hispanics, mid-to-high socioeconomic status households, and foreign-born citizens were associated with elevated risks. Hispanic ethnicity intersected with non-White racial identification to amplify risks. In contrast, increased concentrations of non-Hispanic Black people and foreign-born non-citizens were not associated with disparate risks. To ameliorate environmental health inequities in this context, research and policy actions must be tailored to the US-Mexico border and consider intersectional positions within the Hispanic population.

Elucidating sources of VOCs in the Capital Region of New York State: Implications to secondary transformation and public health exposure

Exposure to ambient volatile organic compounds (VOCs) in urban areas is of interest because of their potential adverse effects to public health. A study was carried out to elucidate ambient sources of VOCs in the Capital Region of New York State for the period 2015-2019. A combined dataset of VOCs and PM_2.5 species was used in positive matrix factorization (PMF) model to better interpret the complex nature of different sources. Ten sources were revealed, where background source (3.8 μg/m³, 30%) was the largest contributor to VOCs, followed by petroleum-related emissions (2.9 μg/m³, 22%) and pyrolyzed oxygen (OP)-Elemental Carbon (EC2)-aldehydes-rich (2.7 μg/m³, 21%). Other notable VOC sources included methyl ethyl ketone (MEK)-rich, vehicular traffic, and biomass burning. Both OP-EC2-aldehydes-rich and petroleum-related emissions showed notable contribution to ozone (O₃) and secondary organic aerosol (SOA) formation, respectively. Observed mean carcinogenic risk values of benzene and formaldehyde and 95th percentiles risk values of 1,3-butadiene and acetaldehyde were above the USEPA acceptable level of 1x10^-6 but below a tolerable risk of 1x10^-4. Estimated carcinogenic risk values of OP-EC2-aldehydes-rich, vehicular traffic, background and petroleum-related emissions were above the USEPA acceptable cancer risk and posed greater risk to public health (more than 80% of total carcinogenic risk) compared to other sources. Due to lack of some VOC species data (e.g., alkanes, alkenes, terpenes, alcohols), other urban VOC sources e.g., fugitive emissions, fuel evaporation, unburned fuel were not identified. More work is needed to better understand the contribution of VOC sources to O₃ and SOA formation in Albany and surrounding region. Findings can support policy makers in developing appropriate air quality management initiatives for the Capital Region in New York State.

Using Bayesian time-stratified case-crossover models to examine associations between air pollution and "asthma seasons" in a low air pollution environment

Many areas of the United States have air pollution levels typically below Environmental Protection Agency (EPA) regulatory limits. Most health effects studies of air pollution use meteorological (e.g., warm/cool) or astronomical (e.g., solstice/equinox) definitions of seasons despite evidence suggesting temporally-misaligned intra-annual periods of relative asthma burden (i.e., “asthma seasons”). We introduce asthma seasons to elucidate whether air pollutants are associated with seasonal differences in asthma emergency department (ED) visits in a low air pollution environment. Within a Bayesian time-stratified case-crossover framework, we quantify seasonal associations between highly resolved estimates of six criteria air pollutants, two weather variables, and asthma ED visits among 66,092 children ages 5–19 living in South Carolina (SC) census tracts from 2005 to 2014. Results show that coarse particulates (particulate matter <10 μm and >2.5 μm: PM_10-2.5) and nitrogen oxides (NO_x) may contribute to asthma ED visits across years, but are particularly implicated in the highest-burden fall asthma season. Fine particulate matter (<2.5 μm: PM_2.5) is only associated in the lowest-burden summer asthma season. Relatively cool and dry conditions in the summer asthma season and increased temperatures in the spring and fall asthma seasons are associated with increased ED visit odds. Few significant associations in the medium-burden winter and medium-high-burden spring asthma seasons suggest other ED visit drivers (e.g., viral infections) for each, respectively. Across rural and urban areas characterized by generally low air pollution levels, there are acute health effects associated with particulate matter, but only in the summer and fall asthma seasons and differing by PM size.

Human Chemical Exposure from Background Emissions in the United States and the Implication for Quantifying Risks from Marginal Emission Increase

The linear dose-response relationship has long been assumed in assessments of health risk from an incremental chemical emission relative to background emissions. In this study, we systematically examine the relevancy of such an assumption with real-world data. We used the reported emission data, as background emissions, from the 2017 U.S. National Emission Inventory for 95 organic chemicals to estimate the central tendencies of exposures of the general U.S. population. Previously published nonlinear dose-response relationships for chemicals were used to estimate health risk from exposure. We also explored and identified four intervals of exposure in which the nonlinear dose-response relationship may be linearly approximated with fixed slopes. Predicted rates of exposure to these 95 chemicals are all within the lowest of the four intervals and associated with low health risk. The health risk may be overestimated if a slope on the dose-response relationship extrapolated from toxicological assays based on high response rates is used for a marginal increase in emission not substantially higher than background emissions. To improve the confidence of human health risk estimates for chemicals, future efforts should focus on deriving a more accurate dose-response relationship at lower response rates and interface it with exposure assessments.

Convergence of COVID-19 and chronic air pollution risks: Racial/ethnic and socioeconomic inequities in the U.S

Recent research suggests greater COVID-19 prevalence in areas burdened with higher exposure to chronic air pollution, but previous studies have not examined if socially disadvantaged populations are more likely to reside in communities located at the convergence of both COVID-19 and air pollution health risks. This article presents a national scale U.S. study that investigates whether racial/ethnic minorities, socioeconomically deprived residents, and other vulnerable groups are significantly overrepresented in counties where significantly higher COVID-19 incidence spatially coincides with higher respiratory health risks from outdoor exposure to hazardous air pollutants (HAPs). COVID-19 data from the Johns Hopkins Center for Systems Science and Engineering database are linked to respiratory risk estimates from the U.S. Environmental Protection Agency's National Air Toxics Assessment and variables from the 2018 American Community Survey. Bivariate local measures of spatial association are implemented to identify county clusters representing relationships between COVID-19 incidence rate and respiratory risk from HAP exposure. Socio-demographic characteristics of these clusters are compared using bivariate statistical tests and multivariable generalized estimating equations. Counties where greater COVID-19 incidence coincides significantly with higher HAP respiratory risk contain disproportionately higher percentages of non-Hispanic Black, socioeconomically deprived, and uninsured residents than all other U.S. counties, after controlling for spatial clustering, population density, older age, and other contextual factors. These significant socio-demographic inequities represent an important starting point for more detailed investigations of places facing the double burden of elevated COVID-19 prevalence and air pollution exposure, and also emphasize the urgent need to develop mitigation strategies for addressing both COVID-19 and chronic air pollution in socially vulnerable communities.

Cancer risk from air toxics in relation to neighborhood isolation and sociodemographic characteristics: A spatial analysis of the St. Louis metropolitan area, USA

BACKGROUND

A growing body of research has examined relationships between neighborhood characteristics and exposure to air toxics in the United States. However, a limited number of studies have addressed neighborhood isolation, a measure of spatial segregation. We investigated the spatial distribution of carcinogenic air toxics in the St. Louis metropolitan area and tested the hypothesis that neighborhood isolation and sociodemographic characteristics are associated with exposure to carcinogenic air toxics.

METHODS

We obtained lifetime air toxics cancer risk data from the United States Environmental Protection Agency's National Air Toxic Assessment and sociodemographic data from the American Community Survey. We used geographic information systems to identify statistically significant clusters of census tracts with elevated all-site cancer risk due to air toxics in the St. Louis metropolitan area. Relative Risks (RR) were estimated for the association between neighborhood characteristics and air toxic hot spots. Using a local spatial isolation index to evaluate residential segregation, we also evaluated the association between neighborhood racial and economic isolation and air toxic hot spots.

RESULTS

Approximately 14% (85 of the 615) of census tracts had elevated cancer risk due to air toxics (p < 0.01). These air toxic hot spots were independently associated with neighborhoods with high levels of poverty and unemployment and low levels of education. Census tracts with the highest levels of both racial isolation of Blacks and economic isolation of poverty were more likely to be located in air toxic hotspots than those with low combined racial and economic isolation (RR = 5.34; 95% CI = 3.10-9.22).

CONCLUSIONS

These findings provide strong evidence of unequal distribution of carcinogenic air toxics in the St. Louis metropolitan area. Study results may be used to inform public health efforts to eliminate sociodemographic inequalities in exposure to air pollutants.

Examining the Association between Socioeconomic Status and Exposure to Carcinogenic Emissions in Gyeonggi of South Korea: A Multi-Level Analysis

Although South Korea introduced the Pollutant Release and Transfer Register system in 1996, there is relatively limited evidence on how socioeconomic status at both individual and municipal levels is associated with exposure to toxic chemicals in Korea because of limited data sources. Using a multi-level negative binomial model, this study examined the socioeconomic status of both individuals and municipalities with a higher level of exposure to carcinogenic emissions from industrial facilities in Gyeonggi province, South Korea. The results reveal that economic minority individuals (national basic livelihood security recipients, unemployed people, and tenants), municipalities with higher percentages of industrial land use, and foreign-born populations had more facilities that produce carcinogenic emissions. While similar findings have been reported by many environmental justice studies conducted in other countries, this is the first Korean case study that reports the relationship between socioeconomic status at both individual and municipal levels and exposure to toxic chemicals.

Cumulative Risk and Impact Modeling on Environmental Chemical and Social Stressors

PURPOSE OF REVIEW

The goal of this review is to identify cumulative modeling methods used to evaluate combined effects of exposures to environmental chemicals and social stressors. The specific review question is: What are the existing quantitative methods used to examine the cumulative impacts of exposures to environmental chemical and social stressors on health?

RECENT FINDINGS

There has been an increase in literature that evaluates combined effects of exposures to environmental chemicals and social stressors on health using regression models; very few studies applied other data mining and machine learning techniques to this problem. The majority of studies we identified used regression models to evaluate combined effects of multiple environmental and social stressors. With proper study design and appropriate modeling assumptions, additional data mining methods may be useful to examine combined effects of environmental and social stressors.

A Model-to-Monitor Evaluation of 2011 National-Scale Air Toxics Assessment (NATA)

Environmental research has widely utilized the ambient concentrations of hazardous air pollutants (HAPs) modeled by the National-Scale Air Toxics Assessment (NATA) program; however, limited studies have evaluated the model's performance. This study aims to evaluate the model-to-monitor agreement of the 2011 NATA data with the monitoring data reported to the U.S. Environmental Protection Agency's (EPA) Air Quality System (AQS). Concentrations of 27 representative HAPs measured at 274 sites in the U.S. in 2011 were merged with NATA data by census tract. The comparison consisted of two steps for each HAP: first, the model-monitor difference at each site was compared with the limit of quantitation (LOQ); second, the modeled annual average was compared to the 95% confidence interval of the monitored annual average. Nationally, NATA could predict national medians of most HAPs well; however, it was unable to capture high concentrations. At individual sites, a large portion of model-monitor differences was below the LOQs, indicating they were unquantifiable. Model-to-monitor agreement displayed inconsistent patterns in terms of chemical groups or EPA regions and was strongly impacted by the comparison methods. The substantial non-agreements of NATA predictions with monitoring data require caution in environmental epidemiology and justice studies that are based on NATA data.

Incidence and mortality for respiratory cancer and traffic-related air pollution in São Paulo, Brazil

BACKGROUND

Multiple lines of evidence have associated exposure to ambient air pollution with an increased risk of respiratory malignancies. However, there is a dearth of evidence from low-middle income countries, including those within South America, where the social inequalities are more marked.

OBJECTIVES

To quantify the association between exposures to traffic related air pollution and respiratory cancer incidence and mortality within São Paulo, Brazil. Further, we aim to investigate the role of socioeconomic status (SES) upon these outcomes.

METHODS

Cancer incidence between 2002 and 2011 was derived from the population-based cancer registry. Mortality data (between 2002 and 2013) was derived from the Municipal Health Department. A traffic density database and an annual nitrogen dioxide (NO₂) land use regression model were used as markers of exposure. Age-adjusted Binomial Negative Regression models were developed, stratifying by SES and gender.

RESULTS

We observed an increased rate of respiratory cancer incidence and mortality in association with increased traffic density and NO₂ concentrations, which was higher among those regions with the lowest SES. For cancer mortality and traffic exposure, those in the most deprived region, had an incidence rate ratio (IRR) of 2.19 (95% CI: 1.70, 2.82) when comparing the highest exposure centile (top 90%) to the lowest (lowest 25%). By contrast, in the least deprived area, the IRR for the same exposure contrast was.1.07 (95% CI: 0.95, 1.20). For NO₂ in the most deprived regions, the IRR for cancer mortality in the highest exposed group was 1.44 (95% CI: 1.10, 1.88) while in the least deprived area, the IRR for the highest exposed group was 1.11 (95% CI: 1.01, 1.23).

CONCLUSIONS

Traffic density and NO₂ were associated with an increased rate of respiratory cancer incidence and mortality in São Paulo. Residents from poor regions may suffer more from the impact of traffic air pollution.

Ethnic density and cancer: A review of the evidence

Accumulating data suggest that factors in the social environment may be associated with cancer-related outcomes. Ethnic density, defined as the proportion of racial/ethnic minority individuals residing in a given geographic area, is 1 of the most frequently studied social environment factors, but studies on ethnic density and cancer have yielded inconsistent findings. Thus, the objective of the current review was to summarize the extant data on ethnic density and cancer-related outcomes (cancer risk, stage at diagnosis, and mortality) with the aim of identifying pathways by which ethnic density may contribute to outcomes across populations. In general, the findings indicated an association between ethnic density and increased risk for cancers of infectious origin (eg, liver, cervical) but lower risk for breast and colorectal cancers, particularly among Hispanic and Asian Americans. Hispanic ethnic density was associated with greater odds of late-stage cancer diagnosis, whereas black ethnic density was associated with greater mortality. In addition, this review highlights several methodological and conceptual issues surrounding the measurement of ethnic neighborhoods and their available resources. Clarifying the role of neighborhood ethnic density is critical to developing a greater understanding of the health risks and benefits accompanying these environments and how they may affect racial and ethnic disparities in cancer-related outcomes. Cancer 2018;124:1877-903. © 2018 American Cancer Society.

A multivariate analysis of CalEnviroScreen: comparing environmental and socioeconomic stressors versus chronic disease

BACKGROUND

The health-risk assessment paradigm is shifting from single stressor evaluation towards cumulative assessments of multiple stressors. Recent efforts to develop broad-scale public health hazard datasets provide an opportunity to develop and evaluate multiple exposure hazards in combination.

METHODS

We performed a multivariate study of the spatial relationship between 12 indicators of environmental hazard, 5 indicators of socioeconomic hardship, and 3 health outcomes. Indicators were obtained from CalEnviroScreen (version 3.0), a publicly available environmental justice screening tool developed by the State of California Environmental Protection Agency. The indicators were compared to the total rate of hospitalization for 14 ICD-9 disease categories (a measure of disease burden) at the zip code tabulation area population level. We performed principal component analysis to visualize and reduce the CalEnviroScreen data and spatial autoregression to evaluate associations with disease burden.

RESULTS

CalEnviroScreen was strongly associated with the first principal component (PC) from a principal component analysis (PCA) of all 20 variables (Spearman ρ = 0.95). In a PCA of the 12 environmental variables, two PC axes explained 43% of variance, with the first axis indicating industrial activity and air pollution, and the second associated with ground-level ozone, drinking water contamination and PM_2.5. Mass of pesticides used in agriculture was poorly or negatively correlated with all other environmental indicators, and with the CalEnviroScreen calculation method, suggesting a limited ability of the method to capture agricultural exposures. In a PCA of the 5 socioeconomic variables, the first PC explained 66% of variance, representing overall socioeconomic hardship. In simultaneous autoregressive models, the first environmental and socioeconomic PCs were both significantly associated with the disease burden measure, but more model variation was explained by the socioeconomic PCs.

CONCLUSIONS

This study supports the use of CalEnviroScreen for its intended purpose of screening California regions for areas with high environmental exposure and population vulnerability. Study results further suggest a hypothesis that, compared to environmental pollutant exposure, socioeconomic status has greater impact on overall burden of disease.