A Data Structure for the Geography of Community Exposure to Air Pollution PDF Download

Author: Steven Zachary Sidawi
Publisher:
ISBN:
Category :
Languages : en
Pages : 118

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Author:
Publisher:
ISBN:
Category : Geography
Languages : en
Pages : 944

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Author:
Publisher:
ISBN:
Category : Environmental health
Languages : en
Pages : 1490

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Author: National Research Council
Publisher: National Academies Press
ISBN: 0309264146
Category : Social Science
Languages : en
Pages : 421

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The United States is among the wealthiest nations in the world, but it is far from the healthiest. Although life expectancy and survival rates in the United States have improved dramatically over the past century, Americans live shorter lives and experience more injuries and illnesses than people in other high-income countries. The U.S. health disadvantage cannot be attributed solely to the adverse health status of racial or ethnic minorities or poor people: even highly advantaged Americans are in worse health than their counterparts in other, "peer" countries. In light of the new and growing evidence about the U.S. health disadvantage, the National Institutes of Health asked the National Research Council (NRC) and the Institute of Medicine (IOM) to convene a panel of experts to study the issue. The Panel on Understanding Cross-National Health Differences Among High-Income Countries examined whether the U.S. health disadvantage exists across the life span, considered potential explanations, and assessed the larger implications of the findings. U.S. Health in International Perspective presents detailed evidence on the issue, explores the possible explanations for the shorter and less healthy lives of Americans than those of people in comparable countries, and recommends actions by both government and nongovernment agencies and organizations to address the U.S. health disadvantage.

Author: Jennifer Badger
Publisher:
ISBN:
Category :
Languages : en
Pages : 0

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Air pollution is directly linked to death. In December 2020, a UK coroner ruled that air pollution was the cause of a fatal asthma attack that led to the 2013 death of nine-year-old Ella Adoo-Kissi Debrah who lived adjacent to a busy motorway (BBC News, 2022). The assignment of air pollution as the official cause of death on a death certificate was the first of its kind in the world (Reynolds, 2020). Though this was the first official assignment of air pollution as a cause of death, there are numerous studies linking air pollution exposure with mortality all over the world. Before the COVID-19 pandemic, the air pollutant PM 2.5 was identified as the "largest environmental risk factor in the United States" (Goodkind et al. 2019, p. 8780) and the cause of more annual premature deaths than traffic accidents and homicides combined (Goodkind et al. 2019). With the onset of the COVID-19 pandemic, researchers began assessing the impact of air pollution exposure on COVID-19 incidence and death. In a widely received, nationwide study linking air pollution exposure to COVID-19 mortality, Harvard T.H. Chan School of Public Health researchers, Wu et al., produced significant findings linking the impact of long term exposure to PM 2.5 to COVID-19 mortality across the contiguous United States. This 2020 study, published in ScienceAdvances, has been cited over 600 times, covered by 131 news outlets and downloaded over 15,000 times. Georeferenced data is routinely used in public health research such as this, however, the substantive influence of geography in the relationship between the treatment and outcome variable is often not considered in the model specifications, research design, nor the sampling strategy (Goldhagen et al., 2005; Matisziw, Grubesic, and Wei 2008). Additionally, the mechanism of data aggregation to an administrative unit may spatially misrepresent the data (Delmelle et al., 2022). As air pollution is a local, regional, and transboundary phenomenon (Nordenstam et. al, 1998; Goodkind, 2019), spatial autocorrelation, or spatially similar values, in the long term exposure to PM 2.5 among U.S. counties is likely. Despite the inclusion of maps indicating strong spatial trends in the long term exposure to PM 2.5 and COVID-19 mortality, the possible presence of spatial autocorrelation at the local level or spatial heterogeneity at the regional level was not investigated by the authors. Epidemiological studies invoking large, areal units may misrepresent the underlying, spatial processes of environmental health-hazards and produce unreliable treatment effect estimates when relating air pollution exposure to disease (Fotheringham and Wong, 1991; Kolak and Anselin, 2019). In this thesis, the fragility of the Wu et al. treatment effect estimate to unobserved confounding is assessed utilizing an alternative sensitivity analysis framework. This framework revealed that the estimate derived by Wu et al. (2020) is much more fragile to confounding than reported by the authors. Spatial analysis was then applied to investigate the possibility of spatial regimes (e.g. hotspots) in the treatment and outcome variables which may contribute to biased or inefficient treatment effect estimates. Strong levels of spatial autocorrelation and regional spatial heterogeneity in the long term exposure to PM 2.5, and to a lesser extent in the COVID-19 mortality rate, were confirmed by both computational and exploratory spatial data analysis. The highly variable associations between long term exposure to PM 2.5 and COVID-19 Mortality per U.S. Census Region or EPA Climatically Consistent Region delivered the expected result that the relationship between the treatment and outcome variable changes with changes in the sub-National definition of place. An understanding of the geography of the ubiquitous, locally variable and far-reaching PM 2.5, and its related health-hazard risks can contribute to an uncovering of the politics, power relations, and socioenvironments that coproduce differential access to clean air and the resulting uneven health burdens experienced by Black, LatinX, Asian-American, and immigrant communities. This is an essential step towards disentangling the relationships rendering clean air no longer an "open-access good" (V ron, 2006).

Author: Yongwan Chun
Publisher: Routledge
ISBN: 1000346897
Category : Science
Languages : en
Pages : 180

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Uncertainty and context pose fundamental challenges in GIScience and geographic research. Geospatial data are imbued with errors (e.g., measurement and sampling) and various types of uncertainty that often obfuscate any understanding of the effects of contextual or environmental influences on human behaviors and experiences. These errors or uncertainties include those attributable to geospatial data measurement, model specifications, delineations of geographic context in space and time, and the use of different spatiotemporal scales and zonal schemes when analyzing the effects of environmental influences on human behaviors or experiences. In addition, emerging sources of geospatial big data – including smartphone data, data collected by GPS, and various types of wearable sensors (e.g., accelerometers and air pollutant monitors), volunteered geographic information, and/ or location- based social media data (i.e., crowd- sourced geographic information) – inevitably contain errors, and their quality cannot be fully controlled during their collection or production. Uncertainty and Context in GIScience and Geography: Challenges in the Era of Geospatial Big Data illustrates how cutting- edge research explores recent advances in this area, and will serve as a useful point of departure for GIScientists to conceive new approaches and solutions for addressing these challenges in future research. The seven core chapters in this book highlight many challenges and opportunities in confronting various issues of uncertainty and context in GIScience and geography, tackling different topics and approaches. The chapters in this book were originally published as a special issue of the International Journal of Geographical Information Science.

Author: Lixin Li
Publisher: Elsevier
ISBN: 012816526X
Category : Computers
Languages : en
Pages : 336

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Spatiotemporal Analysis of Air Pollution and Its Application in Public Health reviews, in detail, the tools needed to understand the spatial temporal distribution and trends of air pollution in the atmosphere, including how this information can be tied into the diverse amount of public health data available using accurate GIS techniques. By utilizing GIS to monitor, analyze and visualize air pollution problems, it has proven to not only be the most powerful, accurate and flexible way to understand the atmosphere, but also a great way to understand the impact air pollution has in diverse populations. This book is essential reading for novices and experts in atmospheric science, geography and any allied fields investigating air pollution. Introduces readers to the benefits and uses of geo-spatiotemporal analyses of big data to reveal new and greater understanding of the intersection of air pollution and health Ties in machine learning to improve speed and efficacy of data models Includes developing visualizations, historical data, and real-time air pollution in large geographic areas

Author: Pavlos Kanaroglou
Publisher: Routledge
ISBN: 1317051580
Category : Science
Languages : en
Pages : 344

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Presenting current research on spatial epidemiology, this book covers topics such as exposure, chronic disease, infectious disease, accessibility to health care settings and new methods in Geographical Information Science and Systems. For epidemiologists, and for the management and administration of health care settings, it is critical to understand the spatial dynamics of disease. For instance, it is crucial that hospital administrators develop an understanding of the flow of patients over time, especially during an outbreak of a particular disease, so they can plan for appropriate levels of staffing and to carry out adaptive prevention measures. Furthermore, understanding where and why a disease occurs at a certain geographic location is vital for decision makers to formulate policy to increase the accessibility to health services (either by prevention, or adding new facilities). Spatial epidemiology relies increasingly on new methodologies, such as clustering algorithms, visualization and space-time modelling, the domain of Geographic Information Science. Implementation of those techniques appears at an increasing pace in commercial Geographic Information Systems, alongside more traditional techniques that are already part of such systems. This book provides the latest methods in GI Science and their use in health related problems.

Author: H. Patricia Hynes
Publisher: Routledge
ISBN: 1351950177
Category : Social Science
Languages : en
Pages : 215

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Interest in environmental health research conducted with community participation has increased dramatically in recent years. In this book, Doug Brugge and H. Patricia Hynes relate experience of multiple community collaborations across the United States and highlight the lessons to be learned for those involved in or embarking on community-collaborative research. The volume brings together a variety of cases, examining the nature and form that the collaboration took, the scientific findings from the work and the ethical issues that needed to be addressed. Actual cases covered include lead contaminated soil, asthma and housing conditions, the impact of development on environmental health, the impact of radiation hazards, urban gardening, hog farming and diesel exhaust. The concluding section analyses the experiences of those involved and puts their findings into broader context. Community Research in Environmental Health: Lessons in Science, Advocacy and Ethics provides a valuable guide for all those interested and involved in community research.

Author:
Publisher:
ISBN:
Category : Environmental justice
Languages : en
Pages : 208

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