The Associations Among Seasonality, Food Insecurity, And Diet Quality On Type II Diabetes Mellitus Among American Indian Young Adults

Abstract

Introduction: The diabetes epidemic is a national health crisis that has impacted the American Indian (AI) people for over 20 years. Vulnerabilities of each tribal community create the need for unique preventative and management remedies. Numerous socioeconomic determinants account for many health disparities impacting AI population including food insecurity. Objectives: To determine associations among seasonality, food insecurity, diet quality, and diabetes self-management via glycemic control among AI young adults (ages 18-45) with type 2 diabetes (T2DM), living in rural North Dakota, who are members of Turtle Mountain Band of Chippewa Indians. Methods: A descriptive, longitudinal, non-experimental quantitative design was conducted. Participants were asked to complete a demographic survey, have blood drawn for a hemoglobin A1c (HbA1c) to measure glycemic control, and complete standardized and valid measures: the United States Department of Agriculture (USDA) 10-item food security scale to measure food insecurity, and Healthy Eating Index and a 24-hour diet recall to measure. Data were collected online via REDCap, during both the cold (February through April 2022) and warm seasons (May through July 2022). Data were analyzed using SPSS statistical software (version 28) to examine associations and changes in study variables from cold to warm seasons. Results: A total of 10 participants completed the study with 100% study retention. Pearson’s correlation coefficient determined a negative correlation between food insecurity and diet quality and between food insecurity and HbA1c in both cold and warm seasons. During the warm season, there was a negative correlation between food insecurity, diet quality and HbA1c. During both seasons, diet quality had a positive correlation with HbA1c. A paired samples t-test indicated that there was a non-significant difference between seasonality and food insecurity or diet quality or HbA1c. Overall, there were no significant associations among variables at each time point. Conclusion: Diabetes is one of the top health disparities affecting the AI population. Study recruitment efforts were hampered by several factors including COVID-19, which resulted in only 10 people completing this study. Future research is recommended using community-based participatory research approaches among this AI population to establish rapport with the community prior to conducting extensive online surveys.