Geographic Information Systems-Based Approaches to Study Congressional Redistricting in the United States

The ability for the citizens of a nation to determine their own representation has long been regarded as one of the most critical objectives of any electoral system. Without having the assurance of equality in representation, the fundamental nature and operation of the political system is severely undermined. Given the centuries of institutional reforms and population changes in the American system, Congressional Redistricting stands as an institution whereby this promise of effective representation can either be fulfilled or denied. The broad set of processes that encapsulate Congres- sional Redistricting have been discussed, experimented, and modified to achieve clear objectives and have long been understood to be important. Questions remain about how the dynamics which link all of these processes operate and what impact the real- ities of Congressional Redistricting hold for representation in the American system. This dissertation examines three aspects of how Congressional Redistricting in the Untied States operates in accordance with the principle of “One Person, One Vote.” By utilizing data and data analysis techniques of Geographic Information Systems (GIS), this dissertation seeks to address how Congressional Redistricting impacts the principle of one person, one vote from the standpoint of legislator accountability, redistricting institutions, and the promise of effective minority representation.

The environmental justice dimensions of climate change

Nations around the world are considering strategies to mitigate the severe impacts of climate change predicted to occur in the twenty-first century. Many countries, however, lack the wealth, technology, and government institutions to effectively cope with climate change. This study investigates the varying degrees to which developing and developed nations will be exposed to changes in three key variables: temperature, precipitation, and runoff. We use Geographic Information Systems (GIS) analysis to compare current and future climate model predictions on a country level. We then compare our calculations of climate change exposure for each nation to several metrics of political and economic well-being. Our results indicate that the impacts of changes in precipitation and runoff are distributed relatively equally between developed and developing nations. In contrast, we confirm research suggesting that developing nations will be affected far more severely by changes in temperature than developed nations. Our results also suggest that this unequal impact will persist throughout the twenty-first century. Our analysis further indicates that the most significant temperature changes will occur in politically unstable countries, creating an additional motivation for developed countries to actively engage with developing nations on climate mitigation strategies. © 2011, Mary Ann Liebert, Inc.

The increasing impact of human immunodeficiency virus infections, sexually transmitted diseases, and viral hepatitis in Durham County, North Carolina: a call for coordinated and integrated services.

BACKGROUND: Durham County, North Carolina, faces high rates of human immunodeficiency virus (HIV) infection (with or without progression to AIDS) and sexually transmitted diseases (STDs). We explored the use of health care services and the prevalence of coinfections, among HIV-infected residents, and we recorded community perspectives on HIV-related issues. METHODS: We evaluated data on diagnostic codes, outpatient visits, and hospitalizations for individuals with HIV infection, STDs, and/or hepatitis B or C who visited Duke University Hospital System (DUHS). Viral loads for HIV-infected patients receiving care were estimated for 2009. We conducted geospatial mapping to determine disease trends and used focus groups and key informant interviews to identify barriers and solutions to improving testing and care. RESULTS: We identified substantial increases in HIV/STDs in the southern regions of the county. During the 5-year period, 1,291 adults with HIV infection, 4,245 with STDs, and 2,182 with hepatitis B or C were evaluated at DUHS. Among HIV-infected persons, 13.9% and 21.8% were coinfected with an STD or hepatitis B or C, respectively. In 2009, 65.7% of HIV-infected persons receiving care had undetectable viral loads. Barriers to testing included stigma, fear, and denial of risk, while treatment barriers included costs, transportation, and low medical literacy. LIMITATIONS: Data for health care utilization and HIV load were available from different periods. Focus groups were conducted among a convenience sample, but they represented a diverse population. CONCLUSIONS: Durham County has experienced an increase in the number of HIV-infected persons in the county, and coinfections with STDs and hepatitis B or C are common. Multiple barriers to testing/treatment exist in the community. Coordinated care models are needed to improve access to HIV care and to reduce testing and treatment barriers.

Associations between BMI and home, school and route environmental exposures estimated using GPS and GIS: do we see evidence of selective daily mobility bias in children?

BACKGROUND: This study examined whether objective measures of food, physical activity and built environment exposures, in home and non-home settings, contribute to children's body weight. Further, comparing GPS and GIS measures of environmental exposures along routes to and from school, we tested for evidence of selective daily mobility bias when using GPS data. METHODS: This study is a cross-sectional analysis, using objective assessments of body weight in relation to multiple environmental exposures. Data presented are from a sample of 94 school-aged children, aged 5-11 years. Children's heights and weights were measured by trained researchers, and used to calculate BMI z-scores. Participants wore a GPS device for one full week. Environmental exposures were estimated within home and school neighbourhoods, and along GIS (modelled) and GPS (actual) routes from home to school. We directly compared associations between BMI and GIS-modelled versus GPS-derived environmental exposures. The study was conducted in Mebane and Mount Airy, North Carolina, USA, in 2011. RESULTS: In adjusted regression models, greater school walkability was associated with significantly lower mean BMI. Greater home walkability was associated with increased BMI, as was greater school access to green space. Adjusted associations between BMI and route exposure characteristics were null. The use of GPS-actual route exposures did not appear to confound associations between environmental exposures and BMI in this sample. CONCLUSIONS: This study found few associations between environmental exposures in home, school and commuting domains and body weight in children. However, walkability of the school neighbourhood may be important. Of the other significant associations observed, some were in unexpected directions. Importantly, we found no evidence of selective daily mobility bias in this sample, although our study design is in need of replication in a free-living adult sample.