4 research outputs found
Response to Comment on Hofer et al. International Comparison of Smoking and Metabolic Control in Patients With Type 1 Diabetes. Diabetes Care 2016;39:e177-e178
Five heterogeneous HbA1c trajectories from childhood to adulthood in youth with type 1 diabetes from three different continents: a group-based modeling approach
OBJECTIVES:Only a fraction of youth meet established targets for glycemic control; many experience deteriorating control over time. We compared trajectories of hemoglobin A1c (HbA1c) among youth from three trans-continental type 1 diabetes (T1D) registries and identified clinical variables associated with the odds of following increasing vs stable trajectories. RESEARCH DESIGN AND METHODS:Analyses included longitudinal data from 15 897 individuals age 8 to 18 with T1D for at least 2 years and HbA1c measurements in at least 5 years during the observation period. Cohorts were selected from Australasian Diabetes Data Network (ADDN; Australia), German/Austrian/Luxembourgian Diabetes-Patienten-Verlaufsdokumentation initiative (DPV; Germany/Austria/Luxembourga), and the T1D Exchange Clinic Network (T1DX; US) clinic registries. Group-based trajectory modeling and multivariable logistic regression identified unique HbA1c trajectories and their predictors. RESULTS:Five heterogeneous trajectories of glycemic control in each registry were identified: low, intermediate, high stable; intermediate and high increasing. The overall HbA1c level for each trajectory group tended to be lowest in the DPV, higher in the ADDN, and highest in the T1DX. The absolute level of HbA1c and the proportion of individuals within each trajectory varied across registries: 17% to 22% of individuals followed an increasing trajectory. Compared with maintaining a stable trajectory, following an increasing trajectory was significantly associated with ethnic minority status, lower height z-score, higher BMI z-score, insulin injection therapy, and the occurrence of severe hypoglycemia; however, these factors were not consistent across the three registries. CONCLUSIONS:We report the first multinational registry-based comparison of glycemic control trajectories among youth with T1D from three continents and identify possible targets for intervention in those at risk of an increasing HbA1c trajectory.Mark A. Clements, Anke Schwandt, Kim C. Donaghue, Kellee Miller, Ursula Lück, Jennifer J. Couper ... et al
Longitudinal trajectories of BMI z-score: an international comparison of 11,513 Australian, American and German/Austrian/Luxembourgian youth with type 1 diabetes
BACKGROUND:BMI fluctuations during puberty are common. Data on individual change in BMI from childhood to young adulthood are limited in youth with type 1 diabetes. OBJECTIVES:To compare longitudinal trajectories of body mass index z score (BMIz) from childhood to adolescence across three registries spanning five countries. METHODS:Data sources: T1DX (USA), DPV (Germany/Austria/Luxembourg) and ADDN (Australia). The analysis included 11,513 youth with type 1 diabetes, duration >1 year, at least one BMI measure at baseline (age 8-10 years) and >5 aggregated BMI measures by year of age during follow-up until age 17 years. BMIz was calculated based on WHO charts. Latent class growth modelling was used to identify subgroups following a similar trajectory of BMIz over time. RESULTS:Five distinct trajectories of BMIz were present in the T1DX and ADDN cohorts, while six trajectories were identified in the DPV cohort. Boys followed more often a low/near-normal pattern while elevated BMIz curves were more likely in girls (ADDN; DPV). For T1DX cohort, no sex differences were observed. Comparing the reference group (BMIz ~0) with the other groups during puberty, higher BMIz was significantly associated with older age at T1D onset, racial/ethnic minority and elevated HbA1c (all p<0.05). CONCLUSION:This multinational study presents unique BMIz trajectories in youth with T1D across three continents. The prevalence of overweight and the longitudinal persistence of overweight support the need for close monitoring of weight and nutrition in this population. The international and individual differences likely result from diverse genetic, environmental and therapeutic factors.Helen Phelan, Nicole C. Foster, Anke Schwandt, Jennifer J. Couper, Steven Willi, Peter Kroschwald ... et al
