A Decade of Disparities in Diabetes Technology Use and HbA1c in Pediatric Type 1 Diabetes: A Transatlantic Comparison
OBJECTIVE As diabetes technology use in youth increases worldwide, inequalities in access may exacerbate disparities in hemoglobin A1c (HbA1c). We hypothesized that an increasing gap in diabetes technology use by socioeconomic status (SES) would be associated with increased HbA1c disparities. RESEAR...
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| Published in | Diabetes care Vol. 44; no. 1; pp. 133 - 140 |
|---|---|
| Main Authors | , , , , , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
Alexandria
American Diabetes Association
01.01.2021
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| Subjects | |
| Online Access | Get full text |
| ISSN | 0149-5992 1935-5548 1935-5548 |
| DOI | 10.2337/dc20-0257 |
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| Abstract | OBJECTIVE As diabetes technology use in youth increases worldwide, inequalities in access may exacerbate disparities in hemoglobin A1c (HbA1c). We hypothesized that an increasing gap in diabetes technology use by socioeconomic status (SES) would be associated with increased HbA1c disparities. RESEARCH DESIGN AND METHODS Participants aged <18 years with diabetes duration ≥1 year in the Type 1 Diabetes Exchange (T1DX, U.S., 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 to 2016–2018. RESULTS HbA1c 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 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. CONCLUSIONS 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 past decade. Associations of SES with technology use and HbA1c were weaker in the DPV registry. |
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| AbstractList | OBJECTIVE As diabetes technology use in youth increases worldwide, inequalities in access may exacerbate disparities in hemoglobin A1c (HbA1c). We hypothesized that an increasing gap in diabetes technology use by socioeconomic status (SES) would be associated with increased HbA1c disparities. RESEARCH DESIGN AND METHODS Participants aged <18 years with diabetes duration ≥1 year in the Type 1 Diabetes Exchange (T1DX, U.S., 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 to 2016–2018. RESULTS HbA1c 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 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. CONCLUSIONS 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 past decade. Associations of SES with technology use and HbA1c were weaker in the DPV registry. As diabetes technology use in youth increases worldwide, inequalities in access may exacerbate disparities in hemoglobin A1c (HbA1c). We hypothesized that an increasing gap in diabetes technology use by socioeconomic status (SES) would be associated with increased HbA1c disparities.OBJECTIVEAs diabetes technology use in youth increases worldwide, inequalities in access may exacerbate disparities in hemoglobin A1c (HbA1c). We hypothesized that an increasing gap in diabetes technology use by socioeconomic status (SES) would be associated with increased HbA1c disparities.Participants aged <18 years with diabetes duration ≥1 year in the Type 1 Diabetes Exchange (T1DX, U.S., 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 to 2016-2018.RESEARCH DESIGN AND METHODSParticipants aged <18 years with diabetes duration ≥1 year in the Type 1 Diabetes Exchange (T1DX, U.S., 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 to 2016-2018.HbA1c 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 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.RESULTSHbA1c 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 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.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 past decade. Associations of SES with technology use and HbA1c were weaker in the DPV registry.CONCLUSIONSAlthough 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 past decade. Associations of SES with technology use and HbA1c were weaker in the DPV registry. |
| Author | Walker, Ashby Auzanneau, Marie Maier, Werner Rosenbauer, Joachim Addala, Ananta Holl, Reinhard W. Maahs, David M. Foster, Nicole Miller, Kellee Kapellen, Thomas |
| Author_xml | – sequence: 1 givenname: Ananta orcidid: 0000-0002-0508-4309 surname: Addala fullname: Addala, Ananta organization: Division of Pediatric Endocrinology, Stanford University, Stanford, CA – sequence: 2 givenname: Marie orcidid: 0000-0002-5906-6579 surname: Auzanneau fullname: Auzanneau, Marie organization: University of Ulm, Institute of Epidemiology and Medical Biometry, ZIBMT, Ulm, Germany, German Center for Diabetes Research (DZD), Neuherberg, Germany – sequence: 3 givenname: Kellee surname: Miller fullname: Miller, Kellee organization: Jaeb Center for Health Research, Tampa, FL – sequence: 4 givenname: Werner surname: Maier fullname: Maier, Werner organization: German Center for Diabetes Research (DZD), Neuherberg, Germany, Helmholtz Zentrum München - German Research Center for Environmental Health, Institute of Health Economics and Health Care Management, Neuherberg, Germany – sequence: 5 givenname: Nicole surname: Foster fullname: Foster, Nicole organization: Jaeb Center for Health Research, Tampa, FL – sequence: 6 givenname: Thomas surname: Kapellen fullname: Kapellen, Thomas organization: University of Leipzig, Department of Women and Child Health, Hospital for Children and Adolescents, Leipzig, Germany – sequence: 7 givenname: Ashby surname: Walker fullname: Walker, Ashby organization: Health Equity Initiatives, UF Diabetes Institute, University of Florida, Gainesville, FL – sequence: 8 givenname: Joachim surname: Rosenbauer fullname: Rosenbauer, Joachim organization: German Center for Diabetes Research (DZD), Neuherberg, Germany, Leibniz Center for Diabetes Research at Heinrich Heine University, Institute for Biometrics and Epidemiology, German Diabetes Center, Düsseldorf, Germany – sequence: 9 givenname: David M. surname: Maahs fullname: Maahs, David M. organization: Division of Pediatric Endocrinology, Stanford University, Stanford, CA, Stanford Diabetes Research Center, Stanford, CA – sequence: 10 givenname: Reinhard W. surname: Holl fullname: Holl, Reinhard W. organization: University of Ulm, Institute of Epidemiology and Medical Biometry, ZIBMT, Ulm, Germany, German Center for Diabetes Research (DZD), Neuherberg, Germany |
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| Publisher | American Diabetes Association |
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| References | Rosenbauer (2022031222411874600_B23) 2012; 35 Sequeira (2022031222411874600_B31) 2013; 15 Govan (2022031222411874600_B14) 2012; 55 Cheng (2022031222411874600_B29) 2015; 135 Miller (2022031222411874600_B3) 2020; 43 Institute of Medicine (US) Committee on Understanding and Eliminating Racial and Ethnic Disparities in Health Care (2022031222411874600_B27) 2003 Maier (2022031222411874600_B39) 2017; 60 Bergenstal (2022031222411874600_B18) 2016; 316 Valenzuela (2022031222411874600_B34) 2011; 12 Prahalad (2022031222411874600_B10) 2018; 20 Willi (2022031222411874600_B17) 2015; 135 Mair (2022031222411874600_B15) 2019; 62 American Diabetes Association (2022031222411874600_B5) 2019; 42 Hernandez (2022031222411874600_B35) 2019; 321 Messer (2022031222411874600_B32) 2018; 20 Foster (2022031222411874600_B2) 2019; 21 Mackenbach (2022031222411874600_B38) 2018; 115 2022031222411874600_B28 van den Boom (2022031222411874600_B8) 2019; 42 Auzanneau (2022031222411874600_B16) 2018; 41 Schederecker (2022031222411874600_B26) 2019; 9 Maahs (2022031222411874600_B24) 2014; 57 Sherr (2022031222411874600_B6) 2018; 19 Zimmerman (2022031222411874600_B30) 2019; 2 Karges (2022031222411874600_B7) 2017; 318 Brown (2022031222411874600_B20) 2019; 381 Knighton (2022031222411874600_B13) 2016; 4 Bohn (2022031222411874600_B21) 2016; 11 Walker (2022031222411874600_B12) 2018; 61 Nielsen (2022031222411874600_B33) 2019; 42 DeSalvo (2022031222411874600_B1) 2018; 19 Weisman (2022031222411874600_B19) 2017; 5 de Onis (2022031222411874600_B22) 2007; 85 Greene (2022031222411874600_B36) 2015; 372 Noble (2022031222411874600_B25) 2006; 38 Papanicolas (2022031222411874600_B37) 2018; 319 American Diabetes Association (2022031222411874600_B4) 2019; 42 Prahalad (2022031222411874600_B9) 2020; 43 Miller (2022031222411874600_B11) 2020; 22 |
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| Snippet | OBJECTIVE As diabetes technology use in youth increases worldwide, inequalities in access may exacerbate disparities in hemoglobin A1c (HbA1c). We hypothesized... As diabetes technology use in youth increases worldwide, inequalities in access may exacerbate disparities in hemoglobin A1c (HbA1c). We hypothesized that an... |
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| SubjectTerms | Diabetes Diabetes mellitus Diabetes mellitus (insulin dependent) Emerging Technologies: Data Systems and Devices Hemoglobin Pediatrics Regression analysis Research design Socioeconomic factors Socioeconomics Technology utilization |
| Title | A Decade of Disparities in Diabetes Technology Use and HbA1c in Pediatric Type 1 Diabetes: A Transatlantic Comparison |
| URI | https://www.proquest.com/docview/2473438725 https://www.proquest.com/docview/2443880404 https://pubmed.ncbi.nlm.nih.gov/PMC8162452 |
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