Racial–Ethnic Disparities in Diabetes Technology Use Among Young Adults with Type 1 Diabetes

2020 ◽  
Author(s):  
Shivani Agarwal ◽  
Clyde Schechter ◽  
Jeffrey Gonzalez ◽  
Judith A. Long
Keyword(s):  
Type 1 Diabetes ◽  
Young Adults ◽  
Technology Use ◽  
Ethnic Disparities ◽  
Diabetes Technology ◽  
Racial Ethnic

3-OR: Racial/Ethnic Disparities in Diabetes Technology Use in Young Adults (YA) with Type 1 Diabetes (T1D): Multidisciplinary Stakeholder Perspectives and Solutions

Diabetes ◽  
2021 ◽  
Vol 70 (Supplement 1) ◽  
pp. 3-OR
Author(s):  
SHIVANI AGARWAL ◽  
GLADYS CRESPO-RAMOS ◽  
STEPHANIE LEUNG ◽  
MOLLY FINNAN ◽  
TINA PARK ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Young Adults ◽  
Technology Use ◽  
Ethnic Disparities ◽  
Stakeholder Perspectives ◽  
Diabetes Technology ◽  
Racial Ethnic

scholarly journals Racial-Ethnic Inequity in Young Adults With Type 1 Diabetes

2020 ◽  
Vol 105 (8) ◽  
pp. e2960-e2969 ◽  
Author(s):  
Shivani Agarwal ◽  
Lauren G Kanapka ◽  
Jennifer K Raymond ◽  
Ashby Walker ◽  
Andrea Gerard-Gonzalez ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Young Adults ◽  
Technology Use ◽  
Self Management ◽  
Diabetes Distress ◽  
Diabetes Technology ◽  
Racial Ethnic ◽  
Hispanic White ◽  
Hba1c Levels

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 < 0.001). Non-Hispanic Black YA differed from Hispanic, reporting higher diabetes distress and lower self-management (P < 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 < 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.

Racial Disparities in Diabetes Technology Use and Outcomes in Type 1 Diabetes in a Safety-Net Hospital

2021 ◽  
pp. 193229682199581
Author(s):  
Kathryn L Fantasia ◽  
Kamonkiat Wirunsawanya ◽  
Christopher Lee ◽  
Ivania Rizo
Keyword(s):  
Type 1 Diabetes ◽  
Technology Use ◽  
Ethnic Disparities ◽  
Safety Net ◽  
Diabetes Technology ◽  
Safety Net Hospital ◽  
Race Ethnicity ◽  
Racial Ethnic ◽  
White Patients

Background: Limited data exist regarding diabetes technology use among adults with type 1 diabetes (T1D) in urban racially/ethnically diverse safety-net hospitals. We examined racial/ethnic differences in the use of continuous glucose monitor (CGM) and continuous subcutaneous insulin infusion (CSII) in this setting. Methods: A retrospective review of 227 patients ≥ 18 years of age with T1D seen in an urban, safety-net endocrinology clinic during 2016-2017 was completed (mean age: 39; 80% English-speaking; 50% had public insurance). Diabetes technology use, defined as either CGM or CSII or both CGM and CSII, and clinical outcomes were examined by race/ethnicity. Results: Overall, 30% used CGM and 26% used CSII. After adjusting for age, language, insurance, and annual income, diabetes technology use in non-White patients was significantly lower than in White patients, predominantly lower in Black (aOR 0.25 [95% CI 0.11-0.56]) and patients identified as other race/ethnicity (aOR 0.30 [95% CI 0.11-0.77]). At the highest household income level (≥$75,000/y), Black and Hispanic individuals were significantly less likely than White individuals to use diabetes technology ( P < .0007). Mean hemoglobin A1c (HbA1c) was lower in patients using any diabetes technology compared with patients using no technology ( P < .0001). Use of CGM and CSII together was associated with the lowest HbA1c across all racial/ethnic groups. Conclusions: Racial/ethnic disparities in diabetes technology use and glycemic control were observed even after adjusting for sociodemographic factors. Further research should explore barriers to accessing diabetes technology in non-White populations.

4-OR: Racial/Ethnic Disparities in Diabetes Self-Care in Young Adults (YA) with Type 1 Diabetes (T1D)

Diabetes ◽  
2021 ◽  
Vol 70 (Supplement 1) ◽  
pp. 4-OR
Author(s):  
RABAIL SADIQ ◽  
MELISSA FAZZARI ◽  
SHADI NAHVI ◽  
CHINAZO CUNNINGHAM ◽  
SHIVANI AGARWAL
Keyword(s):  
Type 1 Diabetes ◽  
Young Adults ◽  
Self Care ◽  
Ethnic Disparities ◽  
Racial Ethnic

741-P: Racial/Ethnic Disparity in Advanced Diabetes Technology Use in Type 1 Diabetes (T1D): Minority Young Adult (YA) Perspectives on Perceived Access

Diabetes ◽  
2020 ◽  
Vol 69 (Supplement 1) ◽  
pp. 741-P
Author(s):  
GLADYS CRESPO-RAMOS ◽  
VICTORIA MILLER ◽  
JEFFREY S. GONZALEZ ◽  
ALYSSA JANG ◽  
SHIVANI AGARWAL
Keyword(s):  
Type 1 Diabetes ◽  
Young Adult ◽  
Technology Use ◽  
Ethnic Disparity ◽  
Diabetes Technology ◽  
Perceived Access ◽  
Racial Ethnic

1298-P: Unique Patterns of Racial/Ethnic Disparities among Vulnerable Young Adults with Type 1 Diabetes

Diabetes ◽  
2019 ◽  
Vol 68 (Supplement 1) ◽  
pp. 1298-P ◽  
Author(s):  
SHIVANI AGARWAL ◽  
LAUREN KANAPKA ◽  
JENNIFER RAYMOND ◽  
ASHBY F. WALKER ◽  
ANDREA GERARD GONZALEZ ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Young Adults ◽  
Ethnic Disparities ◽  
Racial Ethnic

803-P: Modifiable Diabetes-Specific Factors and Glycemic Control in Economically Vulnerable and Racial/Ethnic Minority Young Adults with Type 1 Diabetes

Diabetes ◽  
2019 ◽  
Vol 68 (Supplement 1) ◽  
pp. 803-P
Author(s):  
SHIVANI AGARWAL ◽  
LAUREN KANAPKA ◽  
JENNIFER RAYMOND ◽  
ASHBY F. WALKER ◽  
ANDREA GERARD GONZALEZ ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Young Adults ◽  
Glycemic Control ◽  
Ethnic Minority ◽  
Specific Factors ◽  
Racial Ethnic

A Decade of Disparities in Diabetes Technology Use and HbA1c in Pediatric Type 1 Diabetes: A Trans-Atlantic Comparison

2020 ◽  
Author(s):  
Ananta Addala ◽  
Marie Auzanneau ◽  
Kellee Miller ◽  
Werner Maier ◽  
Nicole Foster ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Technology Use ◽  
Hemoglobin A1c ◽  
Diabetes Technology ◽  
Design And Methods ◽  
Relationship Of ◽  
The Relationship ◽  
Pediatric Type 1 Diabetes

<b>Objective:</b> As diabetes technology use in youth increases worldwide, inequalities in access may exacerbate disparities in hemoglobin A1c (HbA1c). We hypothesized an increasing gap in diabetes technology use by socioeconomic status (SES) would be associated with increased HbA1c disparities. <p> </p> <p><b>Research Design and Methods: </b>Participants aged <18 years with diabetes duration ≥1 year in the Type 1 Diabetes Exchange (T1DX, US, n=16,457) and Diabetes Prospective Follow-up (DPV, Germany, n=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 HbA1c from 2010-2012 and 2016-2018. </p> <p> </p> <p><b>Results: </b>HbA1c was higher in participants with lower SES (in 2010-2012 & 2016-2018, respectively: 8.0% & 7.8% in Q1 and 7.6% & 7.5% in Q5 for DPV; and 9.0% & 9.3% in Q1 and 7.8% & 8.0% in Q5 for T1DX). For DPV, the association between SES and HbA1c did not change between the two time periods, whereas for T1DX, disparities in HbA1c 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.</p> <p> </p> <p><b>Conclusions: </b>Although causal conclusions cannot be drawn, diabetes technology use is lowest and HbA1c is highest in those of the lowest SES quintile in the T1DX and this difference for HbA1c broadened in the last decade. Associations of SES with technology use and HbA1c were weaker in the DPV registry. </p>

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