Type 2 Diabetes as an Evolutionary Mismatch in Indigenous Populations in the United States
Category: Research Poster
Author(s): Xenia Guardado Rivera
Presenter(s): Xenia Guardado Rivera
Mentors(s): Melissa Raguet-Schofield
An evolutionary mismatch is a formerly advantageous trait that is maladaptive in our current environment. Evolutionary mismatches may result from receiving too much of a formerly rare stimulus such as caloric intake or too little of a formerly common stimulus such as physical activity. The prevalence of Type 2 Diabetes (T2D) has increased globally with disproportionate rates among population groups. Indigenous populations in the United States (U.S.) experience higher rates of T2D than Black and White populations. This paper’s objective is to review existing literature addressing evolutionary mismatch in relation to T2D, and to combine a biological and cultural perspective in understanding the etiology of chronic disease. I first review literature that demonstrates that genetics has been overemphasized as a risk factor in developing T2D. I then examine food insecurity in the Pine Ridge Reservation in South Dakota to better understand what foods are more widely available for Indigenous populations living on the reservation. These areas of focus demonstrate how social inequalities contribute to T2D disparities across populations. I found that the etiology of T2D cannot be determined by ethnoracial groups or genetic predispositions of individuals across populations. When ethnoracial groups were used to determine prevalence of T2D, a number of studies ignored the evidence that differential prevalence of T2D throughout population groups can be substantiated by non-genetic factors. While genetics influence how high the risk factors are for developing T2D, environmental contributors underlie the differences in T2D rates across populations in the U.S. Focusing on dismantling social inequalities can better improve the health outcomes of Indigenous populations in the U.S. rather than channeling resources into looking for genetic explanations that do not exist.