Anna R Kahkoska1, Crystal T Nguyen2, Linda A Adair1, Allison E Aiello3, Kyle S Burger1, John B Buse4, Dana Dabelea5,6, Lawrence M Dolan7, Faisal S Malik8, Amy K Mottl4, Catherine Pihoker8, Beth A Reboussin9, Katherine A Sauder5,6, Michael R Kosorok2,10, Elizabeth J Mayer-Davis1,4. 1. Department of Nutrition, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina. 2. Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina. 3. Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina. 4. Department of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina. 5. Department of Epidemiology, Colorado School of Public Health, Aurora, Colorado. 6. Department of Pediatrics, School of Medicine, University of Colorado, Aurora, Colorado. 7. Division of Endocrinology, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio. 8. Department of Pediatrics, University of Washington, Seattle, Washington. 9. Department of Biostatistics and Data Science, Wake Forest School of Medicine, Winston Salem, North Carolina. 10. Department of Statistics and Operations Research, University of North Carolina at Chapel Hill, North Carolina.
Abstract
CONTEXT: Subclinical and clinical complications emerge early in type 1 diabetes (T1D) and may be associated with obesity and hyperglycemia. OBJECTIVE: Test how longitudinal "weight-glycemia" phenotypes increase susceptibility to different patterns of early/subclinical complications among youth with T1D. DESIGN: SEARCH for Diabetes in Youth observational study. SETTING: Population-based cohort. PARTICIPANTS: Youth with T1D (n = 570) diagnosed 2002 to 2006 or 2008. MAIN OUTCOME MEASURES: Participants were clustered based on longitudinal body mass index z score and HbA1c from a baseline visit and 5+ year follow-up visit (mean diabetes duration: 1.4 ± 0.4 years and 8.2 ± 1.9 years, respectively). Logistic regression modeling tested cluster associations with seven early/subclinical diabetes complications at follow-up, adjusting for sex, race/ethnicity, age, and duration. RESULTS: Four longitudinal weight-glycemia clusters were identified: The Referent Cluster (n = 195, 34.3%), the Hyperglycemia Only Cluster (n = 53, 9.3%), the Elevated Weight Only Cluster (n = 206, 36.1%), and the Elevated Weight With Increasing Hyperglycemia (EWH) Cluster (n = 115, 20.2%). Compared with the Referent Cluster, the Hyperglycemia Only Cluster had elevated odds of dyslipidemia [adjusted odds ratio (aOR) 2.22, 95% CI: 1.15 to 4.29], retinopathy (aOR 9.98, 95% CI: 2.49 to 40.0), and diabetic kidney disease (DKD) (aOR 4.16, 95% CI: 1.37 to 12.62). The EWH Cluster had elevated odds of hypertension (aOR 2.18, 95% CI: 1.19 to 4.00), dyslipidemia (aOR 2.36, 95% CI: 1.41 to 3.95), arterial stiffness (aOR 2.46, 95% CI: 1.09 to 5.53), retinopathy (aOR 5.11, 95% CI: 1.34 to 19.46), and DKD (aOR 3.43, 95% CI: 1.29 to 9.11). CONCLUSIONS: Weight-glycemia phenotypes show different patterns of complications, particularly markers of subclinical macrovascular disease, even in the first decade of T1D.
CONTEXT: Subclinical and clinical complications emerge early in type 1 diabetes (T1D) and may be associated with obesity and hyperglycemia. OBJECTIVE: Test how longitudinal "weight-glycemia" phenotypes increase susceptibility to different patterns of early/subclinical complications among youth with T1D. DESIGN: SEARCH for Diabetes in Youth observational study. SETTING: Population-based cohort. PARTICIPANTS: Youth with T1D (n = 570) diagnosed 2002 to 2006 or 2008. MAIN OUTCOME MEASURES: Participants were clustered based on longitudinal body mass index z score and HbA1c from a baseline visit and 5+ year follow-up visit (mean diabetes duration: 1.4 ± 0.4 years and 8.2 ± 1.9 years, respectively). Logistic regression modeling tested cluster associations with seven early/subclinical diabetes complications at follow-up, adjusting for sex, race/ethnicity, age, and duration. RESULTS: Four longitudinal weight-glycemia clusters were identified: The Referent Cluster (n = 195, 34.3%), the Hyperglycemia Only Cluster (n = 53, 9.3%), the Elevated Weight Only Cluster (n = 206, 36.1%), and the Elevated Weight With Increasing Hyperglycemia (EWH) Cluster (n = 115, 20.2%). Compared with the Referent Cluster, the Hyperglycemia Only Cluster had elevated odds of dyslipidemia [adjusted odds ratio (aOR) 2.22, 95% CI: 1.15 to 4.29], retinopathy (aOR 9.98, 95% CI: 2.49 to 40.0), and diabetic kidney disease (DKD) (aOR 4.16, 95% CI: 1.37 to 12.62). The EWH Cluster had elevated odds of hypertension (aOR 2.18, 95% CI: 1.19 to 4.00), dyslipidemia (aOR 2.36, 95% CI: 1.41 to 3.95), arterial stiffness (aOR 2.46, 95% CI: 1.09 to 5.53), retinopathy (aOR 5.11, 95% CI: 1.34 to 19.46), and DKD (aOR 3.43, 95% CI: 1.29 to 9.11). CONCLUSIONS: Weight-glycemia phenotypes show different patterns of complications, particularly markers of subclinical macrovascular disease, even in the first decade of T1D.
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