Disparities in Glycemic Outcomes Persist in Youth with Type 1 Diabetes and High-Technology Use
Background. Racial disparities are well described in glycemic outcomes in youth with Type 1 diabetes mellites (T1D). Hemoglobin A1c (HbA1c) has some limitations in comparing glycemia across patient groups as there are individual variations in mean glucose and HbA1c. Objective. This study aimed to co...
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Published in | Pediatric diabetes Vol. 2023; no. 1; pp. 1 - 6 |
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Main Authors | , , , |
Format | Journal Article |
Language | English |
Published |
United States
Hindawi
2023
John Wiley & Sons, Inc |
Subjects | |
Online Access | Get full text |
ISSN | 1399-543X 1399-5448 1399-5448 |
DOI | 10.1155/2023/6646582 |
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Abstract | Background. Racial disparities are well described in glycemic outcomes in youth with Type 1 diabetes mellites (T1D). Hemoglobin A1c (HbA1c) has some limitations in comparing glycemia across patient groups as there are individual variations in mean glucose and HbA1c. Objective. This study aimed to compare glycemic metrics obtained from (Dexcom G6) continuous glucose monitor (CGM) device with HbA1c levels controlling for race, age, duration of diabetes, race, insurance status, and insulin pump use with glycemic control. Subjects and Methods. Data analyzed included 188 patients, majority non-Hispanic White (NHW) (n = 147, 78.2%) and majority privately insured (n = 147, 78.2%). Half of the patients were using insulin pumps, (n = 94, 50.0%) and approximately half were female. Median age was 16.6 (interquartile range: 14.2–18.2) years old with a median age of diabetes diagnosis at 9.3-years old. Results. Significant differences were observed between NHW and non-Hispanic Black (NHB) patients in terms of HbA1c, 90-day mean glucose, and 90-day time >250 mg/dL (>13.9 mmol/L) (7.6% vs. 9.2%, 181 mg/dL vs. 220 mg/dL, and 16.3% vs. 34.7%, respectively, p<0.001 for all comparisons). Multiple linear regression analysis was performed to predict the influence of age, duration of diabetes, race, insurance status, and insulin administration on glycemic outcomes. Regression analysis revealed significant equations for all glycemic outcomes, demonstrating a strong correlation (p<0.0001, p=0.0001, and p<0.0001, respectively). However, after controlling for these variables, only race and duration of diabetes remained independently associated with glycemic outcomes, suggesting that these factors strongly influence glycemic control independent of age, sex, insurance, and pump use. Conclusion. Even in a subset of youth with T1D using CGM with high rates of insulin pump use, disparities in glycemic outcomes persist. When evaluating glycemic outcomes, race remained a significant cofactor despite controlling for age, duration of diabetes, sex, insurance status, and insulin administration type. These results add to the existing literature, and demonstrate race remains strong predictor of glycemic outcomes. |
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AbstractList | Background. Racial disparities are well described in glycemic outcomes in youth with Type 1 diabetes mellites (T1D). Hemoglobin A1c (HbA1c) has some limitations in comparing glycemia across patient groups as there are individual variations in mean glucose and HbA1c. Objective. This study aimed to compare glycemic metrics obtained from (Dexcom G6) continuous glucose monitor (CGM) device with HbA1c levels controlling for race, age, duration of diabetes, race, insurance status, and insulin pump use with glycemic control. Subjects and Methods. Data analyzed included 188 patients, majority non-Hispanic White (NHW) (n = 147, 78.2%) and majority privately insured (n = 147, 78.2%). Half of the patients were using insulin pumps, (n = 94, 50.0%) and approximately half were female. Median age was 16.6 (interquartile range: 14.2–18.2) years old with a median age of diabetes diagnosis at 9.3-years old. Results. Significant differences were observed between NHW and non-Hispanic Black (NHB) patients in terms of HbA1c, 90-day mean glucose, and 90-day time >250 mg/dL (>13.9 mmol/L) (7.6% vs. 9.2%, 181 mg/dL vs. 220 mg/dL, and 16.3% vs. 34.7%, respectively, p<0.001 for all comparisons). Multiple linear regression analysis was performed to predict the influence of age, duration of diabetes, race, insurance status, and insulin administration on glycemic outcomes. Regression analysis revealed significant equations for all glycemic outcomes, demonstrating a strong correlation (p<0.0001, p=0.0001, and p<0.0001, respectively). However, after controlling for these variables, only race and duration of diabetes remained independently associated with glycemic outcomes, suggesting that these factors strongly influence glycemic control independent of age, sex, insurance, and pump use. Conclusion. Even in a subset of youth with T1D using CGM with high rates of insulin pump use, disparities in glycemic outcomes persist. When evaluating glycemic outcomes, race remained a significant cofactor despite controlling for age, duration of diabetes, sex, insurance status, and insulin administration type. These results add to the existing literature, and demonstrate race remains strong predictor of glycemic outcomes. Background. Racial disparities are well described in glycemic outcomes in youth with Type 1 diabetes mellites (T1D). Hemoglobin A1c (HbA1c) has some limitations in comparing glycemia across patient groups as there are individual variations in mean glucose and HbA1c. Objective. This study aimed to compare glycemic metrics obtained from (Dexcom G6) continuous glucose monitor (CGM) device with HbA1c levels controlling for race, age, duration of diabetes, race, insurance status, and insulin pump use with glycemic control. Subjects and Methods. Data analyzed included 188 patients, majority non-Hispanic White (NHW) (n = 147, 78.2%) and majority privately insured (n = 147, 78.2%). Half of the patients were using insulin pumps, (n = 94, 50.0%) and approximately half were female. Median age was 16.6 (interquartile range: 14.2–18.2) years old with a median age of diabetes diagnosis at 9.3-years old. Results. Significant differences were observed between NHW and non-Hispanic Black (NHB) patients in terms of HbA1c, 90-day mean glucose, and 90-day time >250 mg/dL (>13.9 mmol/L) (7.6% vs. 9.2%, 181 mg/dL vs. 220 mg/dL, and 16.3% vs. 34.7%, respectively, p < 0.001 for all comparisons). Multiple linear regression analysis was performed to predict the influence of age, duration of diabetes, race, insurance status, and insulin administration on glycemic outcomes. Regression analysis revealed significant equations for all glycemic outcomes, demonstrating a strong correlation ( p < 0.0001 , p = 0.0001 , and p < 0.0001 , respectively). However, after controlling for these variables, only race and duration of diabetes remained independently associated with glycemic outcomes, suggesting that these factors strongly influence glycemic control independent of age, sex, insurance, and pump use. Conclusion. Even in a subset of youth with T1D using CGM with high rates of insulin pump use, disparities in glycemic outcomes persist. When evaluating glycemic outcomes, race remained a significant cofactor despite controlling for age, duration of diabetes, sex, insurance status, and insulin administration type. These results add to the existing literature, and demonstrate race remains strong predictor of glycemic outcomes. Racial disparities are well described in glycemic outcomes in youth with Type 1 diabetes mellites (T1D). Hemoglobin A1c (HbA1c) has some limitations in comparing glycemia across patient groups as there are individual variations in mean glucose and HbA1c.BackgroundRacial disparities are well described in glycemic outcomes in youth with Type 1 diabetes mellites (T1D). Hemoglobin A1c (HbA1c) has some limitations in comparing glycemia across patient groups as there are individual variations in mean glucose and HbA1c.This study aimed to compare glycemic metrics obtained from (Dexcom G6) continuous glucose monitor (CGM) device with HbA1c levels controlling for race, age, duration of diabetes, race, insurance status, and insulin pump use with glycemic control. Subjects and Methods. Data analyzed included 188 patients, majority non-Hispanic White (NHW) (n = 147, 78.2%) and majority privately insured (n = 147, 78.2%). Half of the patients were using insulin pumps, (n = 94, 50.0%) and approximately half were female. Median age was 16.6 (interquartile range: 14.2-18.2) years old with a median age of diabetes diagnosis at 9.3-years old.ObjectiveThis study aimed to compare glycemic metrics obtained from (Dexcom G6) continuous glucose monitor (CGM) device with HbA1c levels controlling for race, age, duration of diabetes, race, insurance status, and insulin pump use with glycemic control. Subjects and Methods. Data analyzed included 188 patients, majority non-Hispanic White (NHW) (n = 147, 78.2%) and majority privately insured (n = 147, 78.2%). Half of the patients were using insulin pumps, (n = 94, 50.0%) and approximately half were female. Median age was 16.6 (interquartile range: 14.2-18.2) years old with a median age of diabetes diagnosis at 9.3-years old.Significant differences were observed between NHW and non-Hispanic Black (NHB) patients in terms of HbA1c, 90-day mean glucose, and 90-day time >250 mg/dL (>13.9 mmol/L) (7.6% vs. 9.2%, 181 mg/dL vs. 220 mg/dL, and 16.3% vs. 34.7%, respectively, p < 0.001 for all comparisons). Multiple linear regression analysis was performed to predict the influence of age, duration of diabetes, race, insurance status, and insulin administration on glycemic outcomes. Regression analysis revealed significant equations for all glycemic outcomes, demonstrating a strong correlation (p < 0.0001, p=0.0001, and p < 0.0001, respectively). However, after controlling for these variables, only race and duration of diabetes remained independently associated with glycemic outcomes, suggesting that these factors strongly influence glycemic control independent of age, sex, insurance, and pump use.ResultsSignificant differences were observed between NHW and non-Hispanic Black (NHB) patients in terms of HbA1c, 90-day mean glucose, and 90-day time >250 mg/dL (>13.9 mmol/L) (7.6% vs. 9.2%, 181 mg/dL vs. 220 mg/dL, and 16.3% vs. 34.7%, respectively, p < 0.001 for all comparisons). Multiple linear regression analysis was performed to predict the influence of age, duration of diabetes, race, insurance status, and insulin administration on glycemic outcomes. Regression analysis revealed significant equations for all glycemic outcomes, demonstrating a strong correlation (p < 0.0001, p=0.0001, and p < 0.0001, respectively). However, after controlling for these variables, only race and duration of diabetes remained independently associated with glycemic outcomes, suggesting that these factors strongly influence glycemic control independent of age, sex, insurance, and pump use.Even in a subset of youth with T1D using CGM with high rates of insulin pump use, disparities in glycemic outcomes persist. When evaluating glycemic outcomes, race remained a significant cofactor despite controlling for age, duration of diabetes, sex, insurance status, and insulin administration type. These results add to the existing literature, and demonstrate race remains strong predictor of glycemic outcomes.ConclusionEven in a subset of youth with T1D using CGM with high rates of insulin pump use, disparities in glycemic outcomes persist. When evaluating glycemic outcomes, race remained a significant cofactor despite controlling for age, duration of diabetes, sex, insurance status, and insulin administration type. These results add to the existing literature, and demonstrate race remains strong predictor of glycemic outcomes. Racial disparities are well described in glycemic outcomes in youth with Type 1 diabetes mellites (T1D). Hemoglobin A1c (HbA1c) has some limitations in comparing glycemia across patient groups as there are individual variations in mean glucose and HbA1c. This study aimed to compare glycemic metrics obtained from (Dexcom G6) continuous glucose monitor (CGM) device with HbA1c levels controlling for race, age, duration of diabetes, race, insurance status, and insulin pump use with glycemic control. . Data analyzed included 188 patients, majority non-Hispanic White (NHW) ( = 147, 78.2%) and majority privately insured ( = 147, 78.2%). Half of the patients were using insulin pumps, ( = 94, 50.0%) and approximately half were female. Median age was 16.6 (interquartile range: 14.2-18.2) years old with a median age of diabetes diagnosis at 9.3-years old. Significant differences were observed between NHW and non-Hispanic Black (NHB) patients in terms of HbA1c, 90-day mean glucose, and 90-day time >250 mg/dL (>13.9 mmol/L) (7.6% vs. 9.2%, 181 mg/dL vs. 220 mg/dL, and 16.3% vs. 34.7%, respectively, < 0.001 for all comparisons). Multiple linear regression analysis was performed to predict the influence of age, duration of diabetes, race, insurance status, and insulin administration on glycemic outcomes. Regression analysis revealed significant equations for all glycemic outcomes, demonstrating a strong correlation ( < 0.0001, =0.0001, and < 0.0001, respectively). However, after controlling for these variables, only race and duration of diabetes remained independently associated with glycemic outcomes, suggesting that these factors strongly influence glycemic control independent of age, sex, insurance, and pump use. Even in a subset of youth with T1D using CGM with high rates of insulin pump use, disparities in glycemic outcomes persist. When evaluating glycemic outcomes, race remained a significant cofactor despite controlling for age, duration of diabetes, sex, insurance status, and insulin administration type. These results add to the existing literature, and demonstrate race remains strong predictor of glycemic outcomes. |
Author | Frey, Blake Nath, Meryl C. Atchison, Joycelyn Schmitt, Jessica A. |
AuthorAffiliation | 2 Department of Pediatrics, University of Alabama at Birmingham, Birmingham, AL 35233, USA 1 UAB Heersink School of Medicine, Birmingham, AL 35233, USA |
AuthorAffiliation_xml | – name: 2 Department of Pediatrics, University of Alabama at Birmingham, Birmingham, AL 35233, USA – name: 1 UAB Heersink School of Medicine, Birmingham, AL 35233, USA |
Author_xml | – sequence: 1 givenname: Meryl C. orcidid: 0000-0002-4614-4830 surname: Nath fullname: Nath, Meryl C. organization: UAB Heersink School of MedicineBirminghamAL 35233USAuab.edu – sequence: 2 givenname: Blake orcidid: 0000-0003-3003-6904 surname: Frey fullname: Frey, Blake organization: UAB Heersink School of MedicineBirminghamAL 35233USAuab.edu – sequence: 3 givenname: Joycelyn orcidid: 0009-0001-2846-593X surname: Atchison fullname: Atchison, Joycelyn organization: Department of PediatricsUniversity of Alabama at BirminghamBirminghamAL 35233USAuab.edu – sequence: 4 givenname: Jessica A. orcidid: 0000-0003-0733-2000 surname: Schmitt fullname: Schmitt, Jessica A. organization: Department of PediatricsUniversity of Alabama at BirminghamBirminghamAL 35233USAuab.edu |
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Cites_doi | 10.2337/dc20-0257 10.2337/dc13-2112 10.1089/dia.2021.0511 10.1542/peds.2014-1774 10.2337/dc09-1440 10.1089/dia.2018.0384 10.7326/M16-2596 10.1001/jamanetworkopen.2021.31278 10.1016/s0022-3476(94)70190-3 10.2337/dc20-1531 10.1111/pedi.12711 |
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Copyright | Copyright © 2023 Meryl C. Nath et al. 2023. This article is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. Copyright © 2023 Meryl C. Nath et al. 2023 |
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Snippet | Background. Racial disparities are well described in glycemic outcomes in youth with Type 1 diabetes mellites (T1D). Hemoglobin A1c (HbA1c) has some... Racial disparities are well described in glycemic outcomes in youth with Type 1 diabetes mellites (T1D). Hemoglobin A1c (HbA1c) has some limitations in... |
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SubjectTerms | Adolescent Age Blood glucose Blood Glucose - analysis Blood Glucose Self-Monitoring Child Diabetes Diabetes mellitus (insulin dependent) Diabetes Mellitus, Type 1 - blood Diabetes Mellitus, Type 1 - drug therapy Diabetes Mellitus, Type 1 - ethnology Female Glucose Glycated Hemoglobin - analysis Glycemic Control Healthcare Disparities - statistics & numerical data Hemoglobin Humans Hypoglycemic Agents - administration & dosage Hypoglycemic Agents - therapeutic use Infusion pumps Insulin Insulin - administration & dosage Insulin Infusion Systems - statistics & numerical data Male Regression analysis White |
Title | Disparities in Glycemic Outcomes Persist in Youth with Type 1 Diabetes and High-Technology Use |
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