Healthcare Travel Burden and Diabetes Management
thesisposted on 2020-08-01, 00:00 authored by James L McCombs
In 2018, 10.5% of the United States population, approximately 34.2 million people, had diabetes, while 13.0% of adults age 18 years or older, about 34.1 million people, had diabetes (1). Diabetes is a complicated disease that requires ongoing care beyond managing blood glucose (A1C) (2). People with diabetes may need to manage changes in diet, physical activity, and medication use, as well as monitor their feet for injuries that may go unnoticed due to diabetic neuropathy (3). Yearly dilated eye exams are recommended to detect and manage diabetic retinopathy and diabetic macular edema (4). The propensity of diabetes to lead to other diseases, poorer health outcomes, high healthcare costs, greater disability, and work impediment make it critical that people with diabetes attain proper health care to manage their diabetes. Transportation is necessary for ongoing healthcare access, so it is important to understand how travel burden affects health outcomes. Travel burden to health care is a subjective concept that can fluctuate due to multiple factors. Distance, travel time, geography, socioeconomic status, disability, and type of transportation used may affect patients’ ability to travel to health care appointments. This current research project will help us to understand the effect of self-reported urban travel burden on a group of low income, racial minority patients with diabetes. The study population for this investigation is drawn from a randomized trial of a diabetes intervention with two years of follow up data for 244 racial minorities with uncontrolled diabetes (A1C ≥ 8%) attending the University of Illinois Medical Center ambulatory network in Chicago (5). Travel burden was assessed by participants responding to the question, “On a scale of 1-4, how much trouble is it for you to get transportation to your primary care doctor at (UIC/Mile Square).” We hypothesized that greater travel burden is associated with high A1C levels (≥ 9%). The aims of this study are to: 1. Determine if self-reported travel burden to primary care provider is associated with A1C levels among the study population during the 2 years of follow up. 2. Determine if self-reported travel burden to primary care provider is associated with A1C levels among the study population with high A1C levels at baseline during the 2 years of follow up. 3. Assess effect modifiers of the association of travel burden with A1C levels. With the inclusion of age and income covariates, this study found a statistically significant longitudinal relationship between self-reported travel burden and patients’ success in achieving lower A1C levels among patients with high A1C levels at baseline. Models with age and income covariates found a significant difference between “no problem” and “a lot of trouble” travel burden. The effect of “little trouble” and “some trouble” did not differ significantly from “no trouble” travel burden in any models. Having low diabetes support from friends and family, low income, and being obese were each associated with travel burden having a stronger relationship with A1C levels. Our findings add to the literature by finding an association between self-reported travel burden and A1C levels for racial minorities with diabetes in an urban setting.