Quantifying Diabetes Disparities Related to American Indian and Alaskan Native Residency on Reservations

35 pagesAmerican Indians and Alaskan Natives (AI/AN) have the highest diabetes rate of any racial group in the United States. Rates range from 6.0% in some Alaskan Natives to 29.3% for tribes in Southern Arizona (Edwards and Patchell, 2009), suggesting that environmental and social effects may exacerbate health disparities. Due to the violent and traumatic events that created the reservation system, there are likely enduring conditions that deepen health disparities for AI/AN within these areas. Diabetes serves as the outcome of interest. The current thesis examines the correlation between living in a Census-designated American Indian Area (AIA) and having a diabetes diagnosis. Data from the 2015-2018 series of the National Survey on Drug Use and Health was run in logistic regression models to determine if residency in AIAs influences diabetes rates. These models quantify the severity of this inequality while controlling for other demographic factors such as age, family income, gender, education, and metropolitan status. The results show that AI/AN living in AIAs are anywhere between 1.595 - 1.764 times more likely to have diabetes than AI/AN outside of AIAs, depending on the controls. All models demonstrate statistical significance for the relationship between AIA and diabetes, showing that living in reservation-like areas is correlated with conditions that likely contribute to diabetes disparities. Potential explanations for inequalities include lack of nutritious food sources, environmental stress, suboptimal prenatal conditions, and other socio-environmental conditions. This expands the current notion of factors that influence health, especially in the cultural context of AI/AN. These findings serve as a starting point for further qualitative research to explore social processes creating environmental inequalities and exacerbating health disparities. Exploring these mechanisms is crucial for creating effective policies and interventions that reduce diabetes disparities for AI/AN in their appropriate social contexts