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      A Decade of Disparities in Diabetes Technology Use and HbA 1c in Pediatric Type 1 Diabetes: A Transatlantic Comparison

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          Abstract

          OBJECTIVE

          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 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 HbA 1c from 2010–2012 to 2016–2018.

          RESULTS

          HbA 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.

          CONCLUSIONS

          Although 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.

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          Most cited references38

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          State of Type 1 Diabetes Management and Outcomes from the T1D Exchange in 2016–2018

          To provide a snapshot of the profile of adults and youth with type 1 diabetes (T1D) in the United States and assessment of longitudinal changes in T1D management and clinical outcomes in the T1D Exchange registry.
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            Development of a WHO growth reference for school-aged children and adolescents.

            To construct growth curves for school-aged children and adolescents that accord with the WHO Child Growth Standards for preschool children and the body mass index (BMI) cut-offs for adults. Data from the 1977 National Center for Health Statistics (NCHS)/WHO growth reference (1-24 years) were merged with data from the under-fives growth standards' cross-sectional sample (18-71 months) to smooth the transition between the two samples. State-of-the-art statistical methods used to construct the WHO Child Growth Standards (0-5 years), i.e. the Box-Cox power exponential (BCPE) method with appropriate diagnostic tools for the selection of best models, were applied to this combined sample. The merged data sets resulted in a smooth transition at 5 years for height-for-age, weight-for-age and BMI-for-age. For BMI-for-age across all centiles the magnitude of the difference between the two curves at age 5 years is mostly 0.0 kg/m(2) to 0.1 kg/m(2). At 19 years, the new BMI values at +1 standard deviation (SD) are 25.4 kg/m(2) for boys and 25.0 kg/m(2) for girls. These values are equivalent to the overweight cut-off for adults (> or = 25.0 kg/m(2)). Similarly, the +2 SD value (29.7 kg/m(2) for both sexes) compares closely with the cut-off for obesity (> or = 30.0 kg/m(2)). The new curves are closely aligned with the WHO Child Growth Standards at 5 years, and the recommended adult cut-offs for overweight and obesity at 19 years. They fill the gap in growth curves and provide an appropriate reference for the 5 to 19 years age group.
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              Health Care Spending in the United States and Other High-Income Countries

              Health care spending in the United States is a major concern and is higher than in other high-income countries, but there is little evidence that efforts to reform US health care delivery have had a meaningful influence on controlling health care spending and costs.
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                Author and article information

                Journal
                Diabetes Care
                Diabetes Care
                diacare
                dcare
                Diabetes Care
                Diabetes Care
                American Diabetes Association
                0149-5992
                1935-5548
                January 2021
                16 September 2020
                : 44
                : 1
                : 133-140
                Affiliations
                [1] 1Division of Pediatric Endocrinology, Stanford University, Stanford, CA
                [2] 2University of Ulm, Institute of Epidemiology and Medical Biometry, ZIBMT, Ulm, Germany
                [3] 3German Center for Diabetes Research (DZD), Neuherberg, Germany
                [4] 4Jaeb Center for Health Research, Tampa, FL
                [5] 5Helmholtz Zentrum München - German Research Center for Environmental Health, Institute of Health Economics and Health Care Management, Neuherberg, Germany
                [6] 6University of Leipzig, Department of Women and Child Health, Hospital for Children and Adolescents, Leipzig, Germany
                [7] 7Health Equity Initiatives, UF Diabetes Institute, University of Florida, Gainesville, FL
                [8] 8Leibniz Center for Diabetes Research at Heinrich Heine University, Institute for Biometrics and Epidemiology, German Diabetes Center, Düsseldorf, Germany
                [9] 9Stanford Diabetes Research Center, Stanford, CA
                Author notes
                Corresponding author: Ananta Addala, aaddala@ 123456stanford.edu
                Author information
                https://orcid.org/0000-0002-0508-4309
                https://orcid.org/0000-0002-5906-6579
                Article
                200257
                10.2337/dc20-0257
                8162452
                32938745
                08a1a0c3-39d2-4f3a-9c96-8aaf75b0f685
                © 2020 by the American Diabetes Association

                Readers may use this article as long as the work is properly cited, the use is educational and not for profit, and the work is not altered. More information is available at https://www.diabetesjournals.org/content/license.

                History
                : 5 February 2020
                : 7 August 2020
                Page count
                Figures: 2, Tables: 1, Equations: 0, References: 39, Pages: 8
                Funding
                Funded by: Leona M. and Harry B. Helmsley Charitable Trust, DOI https://dx.doi.org/10.13039/100007028;
                Funded by: German Center for Diabetes Research
                Award ID: 82DZD14A02
                Funded by: German Diabetes Association
                Funded by: European Foundation for the Study of Diabetes
                Categories
                0309
                Emerging Technologies: Data Systems and Devices

                Endocrinology & Diabetes
                Endocrinology & Diabetes

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