{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Liese AD"],"funding":["Seattle Children’s Hospital","NCATS NIH HHS","NCCDPHP CDC HHS","Seattle Children's Hospital and the University of Washington","Cincinnati Children&apos;s Hospital Medical Center","National Institutes of Health","South Carolina Clinical and Translational Research Institute, Medical University of South Carolina","Wake Forest University School of Medicine","Centers for Disease Control and Prevention","Ohio Department of Health","Kaiser Permanente Southern California","Marilyn Owsley Clinical Research Center","Cincinnati's Children's Hospital Medical Center","University of Colorado Denver","Kaiser Permanente","National Center for Advancing Translational Sciences","Seattle Children's Hospital","National Institute of Diabetes and Digestive and Kidney Diseases","Wake Forest School of Medicine","HSRD VA","University of Cincinnati","NIDDK NIH HHS","Cincinnati Children's Hospital Medical Center","University of North Carolina at Chapel Hill","University of Colorado","CDC HHS"],"pagination":["461-471"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC9116580"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["56(5)"],"pubmed_abstract":["<h4>Background</h4>Racial/ethnic health inequities have been well-documented among youth and young adults with type 1 diabetes (T1D), yet little is known about how socioeconomic position (SEP) intersects with the risk marker of race/ethnicity to predict inequities in longitudinal glycemic control.<h4>Purpose</h4>To identify patterns of SEP, race/ethnicity, and clinical characteristics that differentiate hemoglobin A1c (HbA1c) trajectories among youth and young adults after T1D diagnosis.<h4>Methods</h4>The SEARCH for Diabetes in Youth cohort includes youth with diabetes diagnosed from 2002 to 2006 and 2008 who were followed through 2015. We analyzed data from 1,313 youth and young adults with T1D with ≥3 HbA1c measures. Classification tree analysis identified patterns of baseline demograph"],"journal":["Annals of behavioral medicine : a publication of the Society of Behavioral Medicine"],"pubmed_title":["Inequalities in Glycemic Control in Youth with Type 1 Diabetes Over Time: Intersectionality Between Socioeconomic Position and Race and Ethnicity."],"pmcid":["PMC9116580"],"funding_grant_id":["U18 DP006133","U01 DP000248","U01 DP000247","U18 DP006134","U01 DP000246","UL1 TR000077","K23 DK119465","UL1 TR000154","U18 DP006136","U01 DP000244","U18DP002708","UL1 Tr001450","UL1 TR001425","DP-15-002","U18 DP002710","R01 DK127208","1U18DP002709","U18 DP006139","U18 DP006138","UC4 DK108173","F30DK113728","R01DK117461","U48/CCU819241-3","U18 DP002714","DP-05-069","UL1 TR000062","P30 DK57516","U01 DP000254","U01 DP000250","U48/CCU919219","U18DP002710-01","U18DP002714","00097","P30 DK057516","U48/CCU419249","U18 DP003256","HIR 10-001","U18 DP002709","U18 DP002708","U48/CCU519239","200-2010-35171","R01 DK117461","UL1 TR00423","DP-10-001","U18DP000247-06A1","U58/CCU019235-4"],"pubmed_authors":["Dabelea D","Bellatorre A","Imperatore G","Lawrence JM","Saydah S","Frongillo EA","Malik FS","Mendoza JA","Liese AD","Reboussin BA","Kahkoska AR"],"additional_accession":[]},"is_claimable":false,"name":"Inequalities in Glycemic Control in Youth with Type 1 Diabetes Over Time: Intersectionality Between Socioeconomic Position and Race and Ethnicity.","description":"<h4>Background</h4>Racial/ethnic health inequities have been well-documented among youth and young adults with type 1 diabetes (T1D), yet little is known about how socioeconomic position (SEP) intersects with the risk marker of race/ethnicity to predict inequities in longitudinal glycemic control.<h4>Purpose</h4>To identify patterns of SEP, race/ethnicity, and clinical characteristics that differentiate hemoglobin A1c (HbA1c) trajectories among youth and young adults after T1D diagnosis.<h4>Methods</h4>The SEARCH for Diabetes in Youth cohort includes youth with diabetes diagnosed from 2002 to 2006 and 2008 who were followed through 2015. We analyzed data from 1,313 youth and young adults with T1D with ≥3 HbA1c measures. Classification tree analysis identified patterns of baseline demograph","dates":{"release":"2022-01-01T00:00:00Z","publication":"2022 May","modification":"2025-04-04T13:46:57.489Z","creation":"2025-04-04T13:46:57.489Z"},"accession":"S-EPMC9116580","cross_references":{"pubmed":["34570884"],"doi":["10.1093/abm/kaab086"]}}