Adiponectin is an adipocytokine with profound antidiabetic and antiatherogenic effects that is decreased in obesity. With the increasing prevalence of obesity and the emergence of related disorders, including type 2 diabetes in children, the regulation of adiponectin and its relationship to childhood obesity is of great interest. In this study we aimed to elucidate the impact of gender, pubertal development, and obesity on adiponectin levels in children. We investigated two phenotypically characterized cohorts of 200 normal weight and 135 obese children and adolescents covering a wide range of age (3.4-17.9 yr) and body mass index (-2.1 to +4.8 sd score). In healthy lean boys, adiponectin levels significantly declined in parallel with physical and pubertal development, subsequently leading to significantly reduced adiponectin levels in adolescent boys compared with girls (5.6 +/- 0.5 vs. 7.1 +/- 0.5 mg/liter; P = 0.03). This decline was inversely related to testosterone (r = -0.42; P < 0.0001) and dehydroepiandrosterone sulfate (r = -0.20; P = 0.0068) serum concentrations and may account for the gender differences seen in adults. Using a stepwise forward multiple regression model, pubertal stage was the strongest independent predictor of adiponectin (r(2) = 0.206; P < 0.0001), with additional influences of body mass index sd score and testosterone. Adiponectin levels were decreased in obese children and adolescents compared with lean peers of corresponding age and pubertal stage (5.18 vs. 7.13 mg/liter; P = 0.015). In obese children, adiponectin levels were closely associated with parameters related to the metabolic syndrome, such as insulin resistance, hyperinsulinemia, blood pressure, and uric acid, in univariate and multivariate analyses, with the insulin sensitivity index being the strongest independent parameter identified by stepwise forward multiple regression (r(2) = 0.226; P < 0.0001). Hence, there is a strong association of adiponectin serum concentrations with obesity, pubertal development, and metabolic parameters in children indicating epidemiological and pathophysiological relevance already in childhood.

Among young patients with type 1 diabetes, insulin pump therapy, compared with insulin injection therapy, was associated with lower risks of severe hypoglycemia and diabetic ketoacidosis and with better glycemic control during the most recent year of therapy. These findings provide evidence for improved clinical outcomes associated with insulin pump therapy compared with injection therapy in children, adolescents, and young adults with type 1 diabetes.

Background: Transferring adolescents with diabetes from pediatric to adult care remains a challenge and the outcome is often unknown. The aims of this study were to determine the patients’ perception of transfer arrangements and to analyze health care use and metabolic control. Methods: A telephone questionnaire was conducted for patients who had been transferred from the pediatric clinic to adult care between 1995 and 2003. Of 161 identified patients, 101 (58 females, 43 males, mean age 22.1 ± 2.4 years) were interviewed. Pediatric case notes and, if available (n = 44), current notes were analyzed to validate answers from the interview. Results: After transfer, 52.5% of patients changed their health care provider at least once. The mean frequency of changes was 1.47. There was a significant decrease in clinic attendance rate after transition (8.5 ± 2.3/years vs. 6.7 ± 3.2/years). Patients criticized the lack of arrangements, poor information about transfer and the specific age for transition (18 years) set by legislation. The transfer was considered a negative experience by 58 patients. The patients assumed their metabolic control (HbA1c) was better than it really was (7.5 ± 1.3% vs. 8.3 ± 1.6%, p < 0.05). Actual HbA1c from case notes pre- and post-transfer did not change significantly (8.5 ± 1.5% vs. 8.4 ± 1.7%, n = 44, p = 0.441). Conclusion: The establishment of transition clinics and closer cooperation between specialists in pediatric and adult medicine is mandatory. Such changes are demanded by patients and would ensure better uptake of health care services after transfer.

Aims/hypothesis While the use of insulin pumps in paediatrics has expanded dramatically, there is still considerable variability among countries in the use of pump technology. The present study sought to describe differences in metabolic control and pump use in young people with type 1 diabetes using data collected in three multicentre registries. Methods Data for the years 2011 and 2012 from 54,410 children and adolescents were collected from the Prospective Diabetes n=26,198), T1D Exchange (T1DX; n=13,755) and the National Paediatric Diabetes Audit (NPDA; n=14,457). The modality of insulin delivery, based on age, sex and ethnic minority status, and the impact of pump use on HbA 1c levels were compared. differences in metabolic control exist across the three large transatlantic registries of paediatric patients with type 1 diabetes, which appears to be due in part to the frequency of insulin pump therapy. Results

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 METHODSParticipants aged <18 years with diabetes duration ‡1 year in the Type 1 Diabetes Exchange (T1DX, U.S., n 5 16,457) and Diabetes Prospective Follow-up (DPV, Germany, n 5 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. RESULTSHbA 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. CONCLUSIONSAlthough 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.

During a 1-year period, an increase in weight among obese children was associated with a decrease in insulin sensitivity. Weight loss was followed by significant improvement in insulin sensitivity for glucose and fat metabolism but only if the SDS-BMI decreased by > or =0.5 during the 1-year period.

In a cohort study, Beate Karges and colleagues find that the association between low hemoglobin A1C and severe hypoglycemia in children and young adults with type 1 diabetes has decreased over the period between 1995 and 2012. Please see later in the article for the Editors' Summary

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