Browsing by Author "McKnight, Molly Xi"
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- Examining the Modifiable Areal Unit Problem: Associations Between Surface Mining and Birth Outcomes in Central Appalachia at Multiple Spatial ScalesMcKnight, Molly Xi (Virginia Tech, 2020-06-19)Health studies often rely on aggregated instead of individual-level data to protect patient privacy. However, aggregated data are subject to the modifiable areal unit problem (MAUP), meaning results of statistical analyses may differ depending on the data's scale and areal unit. Past studies have suggested MAUP is context-specific and analyzing multiple spatial scales may provide richer understandings of examined phenomena. More research is needed to understand the role of scale and areal unit in health-related analyses. This study examines associations between surface mining and birth outcomes from 1989 to 2015 in Central Appalachia at the individual; postal; county; and county-sized, non-administrative scales. Evidence from previous studies suggests associations exist between health outcomes and county-level measures of mining activity. This is the first study to examine associations between mining and birth outcomes at more spatially refined exposure estimates. We identified surface mines using Landsat imagery and geocoded birth records. Airsheds, used to quantify the influence area of potential airborne pollutants from surface mining activity, were built using HYSPLIT4. The frequency values of each airshed that intersected each geocoded birth record were summed. These cumulative frequency airshed values were then aggregated. Finally, we implemented multiple regression models, each at a different scale, to examine associations between airsheds and birth outcomes. Results suggest MAUP has minimal impacts on the statistical results of examining associations between surface mining and birth outcomes in Central Appalachia. Results also indicate surface mining is significantly associated with preterm birth and reduced birthweight at each scale.
- Maternal proximity to Central Appalachia surface mining and birth outcomesButtling, Lauren G.; McKnight, Molly Xi; Kolivras, Korine N.; Ranganathan, Shyam; Gohlke, Julia M. (Wolters Kluwer Health, 2021-02)Maternal residency in Central Appalachia counties with coal production has been previously associated with increased rates of low birth weight (LBW). To refine the relationship between surface mining and birth outcomes, this study employs finer spatiotemporal estimates of exposure.
Methods
We developed characterizations of annual surface mining boundaries in Central Appalachia between 1986 and 2015 using Landsat data. Maternal address on birth records was geocoded and assigned amount of surface mining within a 5 km radius of residence (street-level). Births were also assigned the amount of surface mining within residential ZIP code tabulation area (ZCTA). Associations between exposure to active mining during gestation year and birth weight, LBW, preterm birth (PTB), and term low birth weight (tLBW) were determined, adjusting for outcome rates before active mining and available covariates.Results
The percent of land actively mined within a 5 km buffer of residence (or ZCTA) was negatively associated with birth weight (5 km: β = -14.07 g; 95% confidence interval [CI] = -19.35, -8.79, P = 1.79 × 10-7; ZCTA: β = -9.93 g; 95% CI = -12.54, -7.33, P = 7.94 × 10-14). We also found positive associations between PTB and active mining within 5 km (odds ratio [OR] = 1.06; 95% CI = 1.03, 1.09, P = 1.43 × 10-4) and within ZCTA (OR = 1.04; 95% CI = 1.03, 1.06, P = 9.21 × 10-8). Positive relationships were also found between amount of active mining within 5 km or ZIP code of residence and LBW and tLBW outcomes.Conclusions
Maternal residency near active surface mining during gestation may increase risk of PTB and LBW. - Renewable Energy Facility Siting ProjectMcKnight, Molly Xi (Virginia Tech, 2019-04-26)The American public has become increasingly concerned about climate change. These concerns over the environment and the desire to decrease energy reliance on other countries have resulted in America’s pursuit of renewable forms of energy (Pew Research Center, 2016). One barrier to implementing renewable energy facility siting projects is public resistance as many people consider renewable energy infrastructure unsightly and intrusive. Some people also feel these projects impinge on their rights to the views to which they are accustomed. However, once the construction begins, community members tend to increase their support for the renewable energy site (Pew Research Center, 2016). This project aims to address public concern about renewable energy facilities by creating an interactive web application hosted on ArcGIS Online. The web application allows the public to type in their address and view how the renewable energy facility siting project impacts the views near their homes. Our hope is that this web application can help the public understand the actual effects on their views, and perhaps in some cases, convince the public that renewable energy is not as unsightly as they might think, allowing developers to overcome this initial barrier. GIS software provides the ability to generate 3D scenes, and GIS data sets, which are widely available on servers, provide basic layers that can be draped over a terrain. However, 3D objects on the terrain are not included in these data, so buildings and trees must be generated or collected for the scenes. In this project, we attempted to generate individual trees through extraction from LiDAR data to promote realism. This LiDAR-based methodology appeared to identify individual trees better areas with less dense tree cover than in heavily forested areas. Future plans include determining the accuracy of our individual tree extraction from LiDAR data method, comparing the LiDAR tree extraction method to a raster-based approach, and creating a fully-functional model of one of our renewable energy facility project sites.