Reimagining rurality: Social determinants of health and social connectedness on the Navajo Nation

Authors: Daniel Beene*, University of New Mexico, Yan Lin, University of New Mexico
Topics: Health and Medical, Indigenous Peoples, Rural Geography
Keywords: social determinants of health, critical physical geography, rurality, Tribal lands, GIScience
Session Type: Virtual Paper
Day: 4/11/2021
Start / End Time: 11:10 AM / 12:25 PM
Room: Virtual 40
Presentation File: No File Uploaded

Social determinants of health (SDH) is a diverse and holistic approach to health research that is nonetheless limited by discursively framing humans and the environment as distinct. This limitation can be reconciled by a critical physical geography approach that attends to the cultural context of space and place and its influence on health outcomes. Political ecology, environmental justice, and Marxist-feminist literature problematize the historic power imbalances that generate health disparities, and more-than-human geographies decenter human agency as the primary research focus. A combination of these approaches can in turn allow health research to shift its attention toward the many networks that are navigated in the construction of space and thereby engender more appropriate conceptualizations of social and environmental determinants of health. Using the concept of rurality to capture multiple SDH, I argue that rurality is entirely relative and dependent on perceptions of benefit, risk, and social connectedness. Despite literature that frames rurality as contextual, most spatial models continue to homogenize rurality across cultural landscapes. As such, I will discuss how GIScience methodologies can be leveraged to capture relative rurality on the Navajo Nation, where degrees of rurality are manifested in terms of traditional and nontraditional life-courses, social cohesion, accessibility, and environmental affordance. I will also discuss how the contribution of critical physical geographic interpretations of SDH can be a powerful addition to epidemiologic and other statistical models of health.

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