Improving environmental exposure analysis using cumulative distribution functions and individual geocoding

BACKGROUND: Assessments of environmental exposure and health risks that utilize Geographic Information Systems (GIS) often make simplifying assumptions when using: (a) one or more discrete buffer distances to define the spatial extent of impacted regions, and (b) aggregated demographic data at the level of census enumeration units to derive the characteristics of the potentially exposed population. A case-study of school children in Orange County, Florida, is used to demonstrate how these limitations can be overcome by the application of cumulative distribution functions (CDFs) and individual geocoded locations. Exposure potential for 159,923 school children was determined at the childrens' home residences and at school locations by determining the distance to the nearest gasoline station, stationary air pollution source, and industrial facility listed in the Toxic Release Inventory (TRI). Errors and biases introduced by the use of discrete buffer distances and data aggregation were examined. RESULTS: The use of discrete buffers distances in proximity-based exposure analysis introduced substantial bias in terms of determining the potentially exposed population, and the results are strongly dependent on the choice of buffer distance(s). Comparisons of exposure potential between home and school locations indicated that different buffer distances yield different results and contradictory conclusions. The use of a CDF provided a much more meaningful representation and is not based on the a-priori assumption that any particular distance is more relevant than another. The use of individual geocoded locations also provided a more accurate characterization of the exposed population and allowed for more reliable comparisons among sub-groups. In the comparison of children's home residences and school locations, the use of data aggregated at the census block group and tract level introduced variability as well as bias, leading to incorrect conclusions as to whether exposure potential was higher at school or at home. CONCLUSION: The use of CDFs in distance-based environmental exposure assessment provides more robust results than the use of discrete buffer distances. Unless specific circumstances warrant the use of discrete buffer distances, their applcation should be discouraged in favor of CDFs. The use of aggregated data at the census tract or block group level introduces substantial bias in environmental exposure assessment, which can be reduced through individual geocoding. The use of aggregation should be minimized when individual-level data are available. Existing GIS analysis techniques are well suited to determine CDFs as well as reliably geocode large datasets, and computational issues do not present a barrier for their more widespread use in environmental exposure and risk assessment

Racial, Ethnic, and Socioeconomic Disparities in Exposure to Fast Food in Hillsborough County, Florida

Recent studies have linked the alarming obesity epidemic in the U.S. to the growth of the fast-food restaurant industry, which offers convenient service alongside inexpensive and high-calorie food. As the number of fast-food outlets increases, research demonstrates that their geographic location plays a significant role in creating obesogenic environments, potentially exposing socially disadvantaged groups to unhealthy nutrition choices provided by these outlets. Whereas previous studies have examined the distribution of positive health amenities such as supermarkets and health-food stores, there is a growing need to evaluate the socio-demographic characteristics of neighborhoods that contain negative health entities such as fast-food outlets. Accordingly, this study sought to determine whether access to fast-food restaurants varied by neighborhood racial/ethnic composition and socioeconomic status in Hillsborough County, Florida—an area that is relatively understudied in terms of its food environment and related health implications. Bivariate and multivariate statistical analyses indicated that race and ethnicity play a pervasive role in explaining the prevalence of fast-food outlets in the county. The results reveal a significantly higher density of fast-food outlets near neighborhoods characterized by a larger proportion of racial/ethnic minorities, even after controlling for the effects of socioeconomic factors and locational characteristics. The study underscores the need to consider both the healthy and unhealthy aspects of the food environment in formulating policy solutions for addressing the obesity epidemic

Positive Feedback Regulation Results in Spatial Clustering and Fast Spreading of Active Signaling Molecules on a Cell Membrane

Positive feedback regulation is ubiquitous in cell signaling networks, often leading to binary outcomes in response to graded stimuli. However, the role of such feedbacks in clustering, and in spatial spreading of activated molecules, has come to be appreciated only recently. We focus on the latter, using a simple model developed in the context of Ras activation with competing negative and positive feedback mechanisms. We find that positive feedback, in the presence of slow diffusion, results in clustering of activated molecules on the plasma membrane, and rapid spatial spreading as the front of the cluster propagates with a constant velocity (dependent on the feedback strength). The advancing fronts of the clusters of the activated species are rough, with scaling consistent with the Kardar-Parisi-Zhang (KPZ) equation in one dimension. Our minimal model is general enough to describe signal transduction in a wide variety of biological networks where activity in the membrane-proximal region is subject to feedback regulation.Comment: 37 pages, 8 figures. Journal of Chemical Physics (in press

The Stimulatory Potency of T Cell Antigens Is Influenced by the Formation of the Immunological Synapse

SummaryT cell activation is predicated on the interaction between the T cell receptor and peptide-major histocompatibility (pMHC) ligands. The factors that determine the stimulatory potency of a pMHC molecule remain unclear. We describe results showing that a peptide exhibiting many hallmarks of a weak agonist stimulates T cells to proliferate more than the wild-type agonist ligand. An in silico approach suggested that the inability to form the central supramolecular activation cluster (cSMAC) could underlie the increased proliferation. This conclusion was supported by experiments that showed that enhancing cSMAC formation reduced stimulatory capacity of the weak peptide. Our studies highlight the fact that a complex interplay of factors determines the quality of a T cell antigen

Digital Signaling and Hysteresis Characterize Ras Activation in Lymphoid Cells

Activation of Ras proteins underlies functional decisions in diverse cell types. Two molecules, RasGRP and SOS, catalyze Ras activation in lymphocytes. Binding of active Ras to SOS' allosteric pocket markedly increases SOS' activity establishing a positive feedback loop for SOS-mediated Ras activation. Integrating in silico and in vitro studies, we demonstrate that digital signaling in lymphocytes (cells are “on” or “off”) is predicated upon feedback regulation of SOS. SOS' feedback loop leads to hysteresis in the dose-response curve, which can enable a capacity to sustain Ras activation as stimuli are withdrawn and exhibit “memory” of past encounters with antigen. Ras activation via RasGRP alone is analog (graded increase in amplitude with stimulus). We describe how complementary analog (RasGRP) and digital (SOS) pathways act on Ras to efficiently convert analog input to digital output. Numerous predictions regarding the impact of our findings on lymphocyte function and development are noted.National Institutes of Health (U.S.). Pioneer AwardNational Institutes of Health (U.S.) (1PO1/AI071195/01

Racial Differences in Perceptions of Air Pollution Health Risk: Does Environmental Exposure Matter?

This article extends environmental risk perception research by exploring how potential health risk from exposure to industrial and vehicular air pollutants, as well as other contextual and socio-demographic factors, influence racial/ethnic differences in air pollution health risk perception. Our study site is the Greater Houston metropolitan area, Texas, USA—a racially/ethnically diverse area facing high levels of exposure to pollutants from both industrial and transportation sources. We integrate primary household-level survey data with estimates of excess cancer risk from ambient exposure to industrial and on-road mobile source emissions of air toxics obtained from the U.S. Environmental Protection Agency. Statistical analysis is based on multivariate generalized estimation equation models which account for geographic clustering of surveyed households. Our results reveal significantly higher risk perceptions for non-Hispanic Black residents and those exposed to greater cancer risk from industrial pollutants, and also indicate that gender influences the relationship between race/ethnicity and air pollution risk perception. These findings highlight the need to incorporate measures of environmental health risk exposure in future analysis of social disparities in risk perception

Air Quality and Environmental Injustice in India: Connecting Particulate Pollution to Social Disadvantages

While air pollution levels in India are amongst the highest in the world, the link between exposure to air pollution and social disadvantages has not been systematically examined. Using a distributive environmental justice framework, this study connects fine particulate matter (PM2.5) concentration data derived from satellite observations, a global chemical transport model, and ground-based measurements to district level socio-demographic information from the 2011 Census of India. The research objectives are to determine if annual average PM2.5 concentrations (2010) and recent increases in average PM2.5 concentrations (2010–2016) are unequally distributed with respect to socially disadvantaged population and household groups, after controlling for relevant contextual factors and spatial clustering. Overall, more than 85% of people and households in India reside in districts where international air quality standards for PM2.5 are exceeded. Although PM2.5 concentration levels are significantly higher in more urbanized districts located predominantly in northern India, recent increases have occurred in less urbanized areas located mainly in southern and central India. Multivariable statistical analysis indicated: (1) higher PM2.5 concentration in districts with higher percentages of Scheduled Castes (SCs), young children, and households in poor condition residence and without toilets; and (2) higher PM2.5 increases in less urbanized districts with higher percentages of SCs, females, children, people with disabilities, and households with no toilets. These findings thus highlight the need to consider the role of air pollution in exacerbating the consequences of social disadvantages in India

Vulnerability to the COVID-19 Pandemic for People with Disabilities in the U.S.

This study seeks to examine the relationship between COVID-19 vulnerability and disability status in the U.S. by investigating whether vulnerability to the pandemic is significantly greater in counties containing higher percentages of people with disabilities (PwDs) and those reporting specific types of difficulties, in four timeframes from May 2020 to February 2021. Values of the recently developed U.S. COVID-19 Pandemic Vulnerability Index (PVI) are analyzed with respect to disability variables from the 2019 American Community Survey five-year estimates. Statistical analyses are based on comparing the mean percentages of PwDs across five quintiles of PVI scores and bivariate generalized estimating equations that examine associations between PVI scores and disability characteristics while controlling for geographic clustering. The results indicate that the percentages of people with any disability and multiple disabilities, as well as percentages of PwDs reporting vision, cognitive, ambulatory, self-care, and independent living difficulties, are significantly greater in counties in the highest 20% of the PVI, compared to those in the lowest 20%. The percentages of all these disability variables are significantly and positively associated with PVI scores, suggesting that PwDs were overrepresented in U.S. counties with higher pandemic vulnerability in all four timeframes. These county-level associations emphasize the urgent need for more detailed analyses to examine the adverse impacts of COVID-19 on PwDs and more detailed information to enable such analyses

Environmental Justice Research: Contemporary Issues and Emerging Topics

Environmental justice (EJ) research seeks to document and redress the disproportionate environmental burdens and benefits associated with social inequalities. Although its initial focus was on disparities in exposure to anthropogenic pollution, the scope of EJ research has expanded. In the context of intensifying social inequalities and environmental problems, there is a need to further strengthen the EJ research framework and diversify its application. This Special Issue of the International Journal of Environmental Research and Public Health (IJERPH) incorporates 19 articles that broaden EJ research by considering emerging topics such as energy, food, drinking water, flooding, sustainability, and gender dynamics, including issues in Canada, the UK, and Eastern Europe. Additionally, the articles contribute to three research themes: (1) documenting connections between unjust environmental exposures and health impacts by examining unsafe infrastructure, substance use, and children’s obesity and academic performance; (2) promoting and achieving EJ by implementing interventions to improve environmental knowledge and health, identifying avenues for sustainable community change, and incorporating EJ metrics in government programs; and (3) clarifying stakeholder perceptions of EJ issues to extend research beyond the documentation of unjust conditions and processes. Collectively, the articles highlight potentially compounding injustices and an array of approaches being employed to achieve EJ

Environmental justice implications of industrial hazardous waste generation in India: a national scale analysis

While rising air and water pollution have become issues of widespread public concern in India, the relationship between spatial distribution of environmental pollution and social disadvantage has received less attention. This lack of attention becomes particularly relevant in the context of industrial pollution, as India continues to pursue industrial development policies without sufficient regard to its adverse social impacts. This letter examines industrial pollution in India from an environmental justice (EJ) perspective by presenting a national scale study of social inequities in the distribution of industrial hazardous waste generation. Our analysis connects district-level data from the 2009 National Inventory of Hazardous Waste Generating Industries with variables representing urbanization, social disadvantage, and socioeconomic status from the 2011 Census of India. Our results indicate that more urbanized and densely populated districts with a higher proportion of socially and economically disadvantaged residents are significantly more likely to generate hazardous waste. The quantity of hazardous waste generated is significantly higher in more urbanized but sparsely populated districts with a higher proportion of economically disadvantaged households, after accounting for other relevant explanatory factors such as literacy and social disadvantage. These findings underscore the growing need to incorporate EJ considerations in future industrial development and waste management in India