Coding sustainable neighborhoods : a comparative analysis of LEED for neighborhood development and the healthy development measurement tool
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Neighborhood design has a significant impact on environmental and human health and is largely regulated by the codes developed by various professional organizations. While the sustainability movement as a whole has embraced the mutually beneficial goals of improving environmental and human health, the work of professionals in the environmental and public health fields has remained largely segregated over the past century. The purpose of my thesis is to compare the approach of each field in fostering sustainable neighborhoods through the development and implementation of codes and to quantify both the existing degree of collaboration and the latent potential for further collaboration within these codes. For comparison, I selected LEED for Neighborhood Development and the Healthy Development Measurement Tool to be representative of neighborhood codes generated by the environmental and public health movements, respectively, because they are the most fully developed and widely implemented evaluation systems presently available in each field. In order to investigate how the codes generated in each field compare in their approach, structure, and organization, I first performed a comparative analysis between them. I then performed a content analysis on both codes to quantify the overlap in goals between them. My hypothesis was that each field would exhibit a bias towards goals which explicitly support their own field, but that a significant portion of their goals would simultaneously support the other field. This hypothesis proved to be correct, but most interesting was the significant percentage of shared goals that were left unexpressed. Ultimately, 94% of recommended actions in LEED-ND were related to human health, though it was only explicitly referenced in 25% of the code. Similarly, 74% of recommended actions in the HDMT were related to environmental health, though it was only explicitly mentioned in 33% of the code. My thesis demonstrates that, while both fields already recognize that a small portion of their goals are shared, it is actually likely that nearly all of their goals are shared. By actively acknowledging these shared goals, both fields can potentially benefit from the greater amount of support, resources, and expertise that would become available to them through collaboration.