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.

Coronavirus diease-2019 has disrupted pediatric healthcare. Observation of public health principles are vital. However, coronavirus diease-2019 has had unintended consequences on standard pediatric care. We describe cases of delayed diagnosis of diabetes leading to severe diabetic ketoacidosis; our aim is to highlight the need to apply basic pediatric principles for optimal care.

Background: Diabetes technology use is associated with favorable type 1 diabetes (T1D) outcomes. American youth with public insurance, a proxy for low socioeconomic status, use less diabetes technology than those with private insurance. We aimed to evaluate the role of insurance-mediated provider implicit bias, defined as the systematic discrimination of youth with public insurance, on diabetes technology recommendations for youth with T1D in the United States. Methods: Multi-disciplinary pediatric diabetes providers completed a bias assessment comprised of a clinical vignette and ranking exercises ( n = 39). Provider bias was defined as providers: (1) recommending more technology for those on private insurance versus public insurance or (2) ranking insurance in the top 2 of 7 reasons to offer technology. Bias and provider characteristics were analyzed with descriptive statistics, group comparisons, and multivariate logistic regression. Results: The majority of providers [44.1 ± 10.0 years old, 83% female, 79% non-Hispanic white, 49% physician, 12.2 ± 10.0 practice-years] demonstrated bias ( n = 33/39, 84.6%). Compared to the group without bias, the group with bias had practiced longer (13.4±10.4 years vs 5.7 ± 3.6 years, P = .003) but otherwise had similar characteristics including age (44.4 ± 10.2 vs 42.6 ± 10.1, p = 0.701). In the logistic regression, practice-years remained significant (OR = 1.47, 95% CI [1.02,2.13]; P = .007) when age, sex, race/ethnicity, provider role, percent public insurance served, and workplace location were included. Conclusions: Provider bias to recommend technology based on insurance was common in our cohort and increased with years in practice. There are likely many reasons for this finding, including healthcare system drivers, yet as gatekeepers to diabetes technology, providers may be contributing to inequities in pediatric T1D in the United States.

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

Objective: Continuous glucose monitor (CGM) use is associated with improved glucose control. We describe the effect of continued and interrupted CGM use on hemoglobin A1c (HbA1c) in youth with public insurance. Methods: We reviewed 956 visits from 264 youth with type 1 diabetes (T1D) and public insurance. Demographic data, HbA1c and two-week CGM data were collected. Youth were classified as never user, consistent user, insurance discontinuer, and selfdiscontinuer. Visits were categorized as never-user visit, visit before CGM start, visit after CGM start, visit with continued CGM use, visit with initial loss of CGM, visit with continued loss of CGM, and visit where CGM is regained after loss. Multivariate regression adjusting for age, sex, race, diabetes duration, initial HbA1c, and body mass index were used to calculate adjusted mean and delta HbA1c. Results: Adjusted mean HbA1c was lowest for the consistent user group (HbA1c 8.6%;[95%CI 7.9,9.3]). Delta HbA1c (calculated from visit before CGM start) was lower for visit after CGM start (−0.39%;[95%CI −0.78,−0.02]) and visit with continued CGM use (−0.29%;[95%CI −0.61,0.02]), whereas it was higher for visit with initial loss of CGM (0.40%;[95%CI −0.06,0.86]), visit with continued loss of CGM (0.46%;[95%CI 0.06,0.85]), and visit where CGM is regained after loss (0.57%;[95%CI 0.06,1.10]). Conclusions: Youth with public insurance using CGM have improved HbA1c, but only when CGM use is uninterrupted. Interruptions in use, primarily due to gaps in insurance coverage of CGM, were associated with increased HbA1c. These data support both initial and ongoing coverage of CGM for youth with T1D and public insurance. K E Y W O R D S diabetes technology, health policy, insurance, minority health, pediatric type 1 diabetes 1 | INTRODUCTION Optimal glucose control paired with improved quality of life is an important management goal for youth with type 1 diabetes (T1D) and providers who care for them. 1-3 Incorporation of continuous glucose This work was previously presented in a poster abstract form at the International Society for Pediatric and Adolescent Society's 45th Annual Conference.