As diabetes technology use in youth increases worldwide, inequalities in access may exacerbate disparities in hemoglobin A 1c (HbA 1c ). We hypothesized that an increasing gap in diabetes technology use by socioeconomic status (SES) would be associated with increased HbA 1c disparities. RESEARCH DESIGN AND METHODSParticipants aged <18 years with diabetes duration ‡1 year in the Type 1 Diabetes Exchange (T1DX, U.S., n 5 16,457) and Diabetes Prospective Follow-up (DPV, Germany, n 5 39,836) registries were categorized into lowest (Q1) to highest (Q5) SES quintiles. Multiple regression analyses compared the relationship of SES quintiles with diabetes technology use and HbA 1c from 2010-2012 to 2016-2018. RESULTSHbA 1c was higher in participants with lower SES (in 2010-2012 and 2016-2018, respectively: 8.0% and 7.8% in Q1 and 7.6% and 7.5% in Q5 for DPV; 9.0% and 9.3% in Q1 and 7.8% and 8.0% in Q5 for T1DX). For DPV, the association between SES and HbA 1c did not change between the two time periods, whereas for T1DX, disparities in HbA 1c by SES increased significantly (P < 0.001). After adjusting for technology use, results for DPV did not change, whereas the increase in T1DX was no longer significant. CONCLUSIONSAlthough causal conclusions cannot be drawn, diabetes technology use is lowest and HbA 1c is highest in those of the lowest SES quintile in the T1DX, and this difference for HbA 1c broadened in the past decade. Associations of SES with technology use and HbA 1c were weaker in the DPV registry.

Abstract Context Minority young adults (YA) currently represent the largest growing population with type 1 diabetes (T1D) and experience very poor outcomes. Modifiable drivers of disparities need to be identified, but are not well-studied. Objective To describe racial-ethnic disparities among YA with T1D and identify drivers of glycemic disparity other than socioeconomic status (SES). Design Cross-sectional multicenter collection of patient and chart-reported variables, including SES, social determinants of health, and diabetes-specific factors, with comparison between non-Hispanic White, non-Hispanic Black, and Hispanic YA and multilevel modeling to identify variables that account for glycemic disparity apart from SES. Setting Six diabetes centers across the United States. Participants A total of 300 YA with T1D (18-28 years: 33% non-Hispanic White, 32% non-Hispanic Black, and 34% Hispanic). Main Outcome Racial-ethnic disparity in HbA1c levels. Results Non-Hispanic Black and Hispanic YA had lower SES, higher HbA1c levels, and much lower diabetes technology use than non-Hispanic White YA (P &lt; 0.001). Non-Hispanic Black YA differed from Hispanic, reporting higher diabetes distress and lower self-management (P &lt; 0.001). After accounting for SES, differences in HbA1c levels disappeared between non-Hispanic White and Hispanic YA, whereas they remained for non-Hispanic Black YA (+ 2.26% [24 mmol/mol], P &lt; 0.001). Diabetes technology use, diabetes distress, and disease self-management accounted for a significant portion of the remaining non-Hispanic Black–White glycemic disparity. Conclusion This study demonstrated large racial-ethnic inequity in YA with T1D, especially among non-Hispanic Black participants. Our findings reveal key opportunities for clinicians to potentially mitigate glycemic disparity in minority YA by promoting diabetes technology use, connecting with social programs, and tailoring support for disease self-management and diabetes distress to account for social contextual factors.

Disparities in type 1 diabetes related to use of technologies like continuous glucose monitors (CGMs) and utilization of diabetes care are pronounced based on socioeconomic status (SES), race, and ethnicity. However, systematic reports of perspectives from patients in vulnerable communities regarding barriers are limited. RESEARCH DESIGN AND METHODSTo better understand barriers, focus groups were conducted in Florida and California with adults $18 years old with type 1 diabetes with selection criteria including hospitalization for diabetic ketoacidosis, HbA 1c >9%, and/or receiving care at a Federally Qualified Health Center. Sixteen focus groups were conducted in English or Spanish with 86 adults (mean age 42 ± 16.2 years). Transcript themes and pre-focus group demographic survey data were analyzed. In order of frequency, barriers to diabetes technology and endocrinology care included: 1) provider level (negative provider encounters); 2) system level (financial coverage); and 3) individual level (preferences). RESULTSOver 50% of participants had not seen an endocrinologist in the past year or were only seen once including during hospital visits. In Florida, there was less technology use overall (38% used CGMs in FL and 63% in CA; 43% used pumps in FL and 69% in CA) and significant differences in pump use by SES (P 5 0.02 in FL; P 5 0.08 in CA) and race/ethnicity (P 5 0.01 in FL; P 5 0.80 in CA). In California, there were significant differences in CGM use by race/ethnicity (P 5 0.05 in CA; P 5 0.56 in FL) and education level (P 5 0.02 in CA; P 5 0.90 in FL). CONCLUSIONSThese findings provide novel insights into the experiences of vulnerable communities and demonstrate the need for multilevel interventions aimed at offsetting disparities in diabetes.Health outcomes in type 1 diabetes in the U.S. are profoundly shaped by socioeconomic status (SES), race, and ethnicity from childhood and throughout the life span. People living with type 1 diabetes from low SES households face elevated risks for suboptimal glycemic control, diabetic ketoacidosis (DKA), disease

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IntroductionProject ECHO (Extension for Community Healthcare Outcomes) is a tele-education outreach model that seeks to democratize specialty knowledge to reduce disparities and improve health outcomes. Limited utilization of endocrinologists forces many primary care providers (PCPs) to care for patients with type 1 diabetes (T1D) without specialty support. Accordingly, an ECHO T1D program was developed and piloted in Florida and California. Our goal was to demonstrate the feasibility of an ECHO program focused on T1D and improve PCPs’ abilities to manage patients with T1D.Research design and methodsHealth centers (ie, spokes) were recruited into the ECHO T1D pilot through an innovative approach, focusing on Federally Qualified Health Centers and through identification of high-need catchment areas using the Neighborhood Deprivation Index and provider geocoding. Participating spokes received weekly tele-education provided by the University of Florida and Stanford University hub specialty team through virtual ECHO clinics, real-time support with complex T1D medical decision-making, access to a diabetes support coach, and access to an online repository of diabetes care resources. Participating PCPs completed pre/post-tests assessing diabetes knowledge and confidence and an exit survey gleaning feedback about overall ECHO T1D program experiences.ResultsIn Florida, 12 spoke sites enrolled with 67 clinics serving >1000 patients with T1D. In California, 11 spoke sites enrolled with 37 clinics serving >900 patients with T1D. During the 6-month intervention, 27 tele-education clinics were offered and n=70 PCPs (22 from Florida, 48 from California) from participating spoke sites completed pre/post-test surveys assessing diabetes care knowledge and confidence in diabetes care. There was statistically significant improvement in diabetes knowledge (p≤0.01) as well as in diabetes confidence (p≤0.01).ConclusionsThe ECHO T1D pilot demonstrated proof of concept for a T1D-specific ECHO program and represents a viable model to reach medically underserved communities which do not use specialists.