Mapping environmental injustices: pitfalls and potential of geographic information systems in assessing environmental health and equity.

Geographic Information Systems (GIS) have been used increasingly to map instances of environmental injustice, the disproportionate exposure of certain populations to environmental hazards. Some of the technical and analytic difficulties of mapping environmental injustice are outlined in this article, along with suggestions for using GIS to better assess and predict environmental health and equity. I examine 13 GIS-based environmental equity studies conducted within the past decade and use a study of noxious land use locations in the Bronx, New York, to illustrate and evaluate the differences in two common methods of determining exposure extent and the characteristics of proximate populations. Unresolved issues in mapping environmental equity and health include lack of comprehensive hazards databases; the inadequacy of current exposure indices; the need to develop realistic methodologies for determining the geographic extent of exposure and the characteristics of the affected populations; and the paucity and insufficiency of health assessment data. GIS have great potential to help us understand the spatial relationship between pollution and health. Refinements in exposure indices; the use of dispersion modeling and advanced proximity analysis; the application of neighborhood-scale analysis; and the consideration of other factors such as zoning and planning policies will enable more conclusive findings. The environmental equity studies reviewed in this article found a disproportionate environmental burden based on race and/or income. It is critical now to demonstrate correspondence between environmental burdens and adverse health impacts--to show the disproportionate effects of pollution rather than just the disproportionate distribution of pollution sources

A Multi-level Health Assessment of Flint, Michigan

The quality of the public's general health depends on the accessibility and quality of our public assets, the way that people live, work, learn, grow struggle, and play together (Judy Kurland, 2000). Ecological theory suggests that by evaluating and altering these conditions, it is possible to influence health behavior and, thus, the health outcomes of populations and their constituent individuals. Various aspects of one’s community can either encourage or discourage public health. Accessibility and availability of products, physical characteristics and structures, inaccessible or poorly resourced health services, neighborhood socioeconomics, deteriorated neighborhoods, and the media are all examples of factors that can influence one’s health. In this study the health of the city of Flint was researched by examining the features and characteristics of zip code areas using a variety of data sources and methodologies, including secondary health and census data, neighborhood drive-thrus and photographs, documenting grocery stores prices, and through mapping neighborhood resources and health data using Geographic Information Systems (GIS). Because of the varied nature of the data collected, different data analyses techniques were used. A focused comparison of 5 health issues in two zip codes showed that no one variable in particular stood out as a major correlate of the health differences between the two zip codes. The data suggest that numerous factors jointly influence the health of the population, including lower income, fewer job opportunities, and less desirable neighborhood environment.Master'sSchool of Health Professions and Studies: Health EducationUniversity of Michiganhttp://deepblue.lib.umich.edu/bitstream/2027.42/117760/1/Tropiano.pd

An integrated framework for the geographic surveillance of chronic disease

<p>Abstract</p> <p>Background</p> <p>Geographic public health surveillance is concerned with describing and disseminating geographic information about disease and other measures of health to policy makers and the public. While methodological developments in the geographical analysis of disease are numerous, few have been integrated into a framework that also considers the effects of case ascertainment bias on the effectiveness of chronic disease surveillance.</p> <p>Results</p> <p>We present a framework for the geographic surveillance of chronic disease that integrates methodological developments in the spatial statistical analysis and case ascertainment. The framework uses an hierarchical approach to organize and model health information derived from an administrative health data system, and importantly, supports the detection and analysis of case ascertainment bias in geographic data. We test the framework on asthmatic data from Alberta, Canada. We observe high prevalence in south-western Alberta, particularly among Aboriginal females. We also observe that persons likely mistaken for asthmatics tend to be distributed in a pattern similar to asthmatics, suggesting that there may be an underlying social vulnerability to a variety of respiratory illnesses, or the presence of a diagnostic practice style effect. Finally, we note that clustering of asthmatics tends to occur at small geographic scales, while clustering of persons mistaken for asthmatics tends to occur at larger geographic scales.</p> <p>Conclusion</p> <p>Routine and ongoing geographic surveillance of chronic diseases is critical to developing an understanding of underlying epidemiology, and is critical to informing policy makers and the public about the health of the population.</p

The use of gis to study the spatial variation of diseases: a case of western region, Ghana

The ability to formulate disease control programmes and put strategic action plans into practice has become an important issue for Regional Health Directorates in Ghana. An important factor in disease control programmes is to correlate variations in different communities with environmental factors using spatially reliable data. To achieve this, spatial distribution maps for predominant diseases such as malaria, skin infection, Respiratory Tract Infection (RTI), asthma and diarrhea for the year 2005 were created. In this study, a database of disease statistics and the geographical information representing the boundaries as well as the centre of the administrative units of the Western Region of Ghana were built using cartographic and GIS techniques – choropleth mapping to examine the spatial distribution of the selected diseases. The results show that there is a strong correlation between mining activities and the prevalence of diseases under study in the Western Region

"Whose data is it anyway?" The implications of putting small area-level health and social data online

International audienceThe planetary exospheres are poorly known in their outer parts, since the neutral densities are low compared with the instruments detection capabilities. The exospheric models are thus often the main source of information at such high altitudes. We present a new way to take into account analytically the additional effect of the radiation pressure on planetary exospheres. In a series of papers, we present with an Hamiltonian approach the effect of the radiation pressure on dynamical trajectories, density profiles and escaping thermal flux. Our work is a generalization of the study by Bishop and Chamberlain (1989). In this second part of our work, we present here the density profiles of atomic Hydrogen in planetary exospheres subject to the radiation pressure. We first provide the altitude profiles of ballistic particles (the dominant exospheric population in most cases), which exhibit strong asymmetries that explain the known geotail phenomenon at Earth. The radiation pressure strongly enhances the densities compared with the pure gravity case (i.e. the Chamberlain profiles), in particular at noon and midnight. We finally show the existence of an exopause that appears naturally as the external limit for bounded particles, above which all particles are escaping

17-09 Assessing the Impact of Air Pollution on Public Health Along Transit Routes

Transportation sources account for a large proportion of the pollutants found in most urban areas. Also, transportation activity and intensity appear likely to contribute to the risk of respiratory disease occurrence. This research investigates the impacts of transportation, urban design and socioeconomic characteristics on the risk of air pollution-related respiratory diseases in two of the biggest MSAs (Metropolitan Statistical Areas) in the US, Dallas-Fort Worth (DFW) and Los Angeles at the block group (BG) level, by considering the US Environmental Protection Agency’s respiratory hazard quotient (RHQ) as the dependent variable. The researchers identify thirty candidate indicators of disease risk from previous studies and use them as independent variables in the model. The study applies a three-step modeling including Principal Component Analysis (PCA), Ordinary Least Square (OLS) and Geographically Weighted Regression (GWR) to reach the final model. The results of this study demonstrate strong spatial correlations in the variability in both MSAs which help explain the impact of the indicators such as socioeconomic characteristics, transit access to jobs, and automobile access on the risk of respiratory diseases. The populations living in areas with higher transit access to jobs in urbanized areas and greater automobile access in more rural areas appear more prone to respiratory diseases after controlling for demographic characteristics

Spatial and Multidimensional Visualization of Jeddah Health Resources: A Community Health Assessment of Jeddah City

Jeddah public health resources are struggling to meet the demand of the large populations. The city is suffering from insufficient public health resources along with other health problem, like high rates of some disease, which resulted in an amount of dissatisfaction among some of the health facilities visitors. The absence of a comprehensive Community Health Assessment study of Jeddah public health resources and the fact that health resources are not meeting the needs of the large population created the need to conduct this study. This is an exploratory study that will use the guidance of two frameworks, Mandala of Health and “Access as fit” theories, and take into account all public hospitals and primary clinics provided by the ministry of health (MOH). Availability and accessibility of MOH resources will be assessed according to the Saudi planning standards for the years 2006 – 2010. Furthermore, health professionals’ numbers will be assessed against the demand of some prominent disease cases in each census tract for the years 2006 – 2010. A multidimensional exploration of the data is needed to answer the queries of this study. Thus, Spatial OLAP Visualization and Analysis Tool (SOVAT) is utilized. This tool has the capability of integrating multidimensional databases to maps. It also answers complex queries easily and rapidly and gives results in maps, spreadsheets, and graphs. The exploration resulted in determining that primary clinics are allocated in accordance with populations’ densities with few exceptions. In addition, parts of the city were found to be lacking some facilities or health professionals while few parts were found to be over-served with resources. Finally, it has been found that there is a need to increase the number of hospitals. Additional patterns of the resources have been uncovered due to the multidimensional capability of SOVAT. The tool proved to be efficient and established a much better comprehensive understanding of the health resources. Additionally, it helped interpreting the interaction between the dimensions of the “Access as fit” framework. Nevertheless, some technical skills were needed for a successful data preparation and integration. It could be implemented by MOH as few requirements must be met