Sabine E Hofer1, Klemens Raile2, Elke Fröhlich-Reiterer3, Thomas Kapellen4, Axel Dost5, Joachim Rosenbauer6, Jürgen Grulich-Henn7, Reinhard W Holl8. 1. Department of Pediatrics 1, Medical University of Innsbruck, Innsbruck, Austria. Electronic address: Sabine.E.Hofer@i-med.ac.at. 2. Department of Pediatrics, Experimental and Clinical Research Center, Charite, Berlin, Germany. 3. Department of Pediatrics, Medical University of Graz, Graz, Austria. 4. Department of Pediatrics, University of Leipzig, Leipzig, Germany. 5. Department of Pediatrics, University of Jena, Jena, Germany. 6. Institute for Biometrics and Epidemiology, German Diabetes Center at Heinrich Heine University of Düsseldorf, Düsseldorf, Germany. 7. Department of Pediatrics, University of Heidelberg, Heidelberg, Germany. 8. Institute of Epidemiology and Medical Biometry, University of Ulm, Ulm, Germany.
Abstract
OBJECTIVE: This prospective longitudinal survey was designed to follow patients with diabetes from disease onset in childhood over an extended period of time including puberty until young adulthood with respect to metabolic control. STUDY DESIGN: An electronic diabetes patient documentation system used in diabetes centers in Austria and Germany was utilized for standardized data collection. Complete documentation of metabolic control for prepuberty (≤ 13 years), puberty (14-19 years), and adulthood (≥ 20 years) was available in 1146 patients. RESULTS: Median age at diabetes manifestation was 7.2 (IQR 4.7-9.4) years; 49% were male. In the prepubertal stage, median glycated hemoglobin A1c (HbA1c) was 7.5 (IQR 6.8-8.3), during puberty 8.0 (IQR 7.3-8.9), and after puberty 7.8 (IQR 7.1-9.0). A significant intra-individual correlation was found for prepuberty to puberty HbA1c levels (R = 0.55, P < .001), puberty to adulthood (R = 0.59, P < .001), as well as prepuberty to adulthood (R = 0.30, P < .001). When patients were divided into tertiles of prepubertal HbA1c, HbA1c increased in all 3 groups over time, however, significant group differences tracked into adulthood (P < .001 at all stages). A regression model identified pre-pubertal HbA1c as a significant and relevant predictor of metabolic control in young adulthood adjusted for confounders (P < .001). CONCLUSIONS: This survey provides evidence for long-term tracking of metabolic control from childhood until adulthood, suggesting an early focus on metabolic control.
OBJECTIVE: This prospective longitudinal survey was designed to follow patients with diabetes from disease onset in childhood over an extended period of time including puberty until young adulthood with respect to metabolic control. STUDY DESIGN: An electronic diabetespatient documentation system used in diabetes centers in Austria and Germany was utilized for standardized data collection. Complete documentation of metabolic control for prepuberty (≤ 13 years), puberty (14-19 years), and adulthood (≥ 20 years) was available in 1146 patients. RESULTS: Median age at diabetes manifestation was 7.2 (IQR 4.7-9.4) years; 49% were male. In the prepubertal stage, median glycated hemoglobin A1c (HbA1c) was 7.5 (IQR 6.8-8.3), during puberty 8.0 (IQR 7.3-8.9), and after puberty 7.8 (IQR 7.1-9.0). A significant intra-individual correlation was found for prepuberty to puberty HbA1c levels (R = 0.55, P < .001), puberty to adulthood (R = 0.59, P < .001), as well as prepuberty to adulthood (R = 0.30, P < .001). When patients were divided into tertiles of prepubertal HbA1c, HbA1c increased in all 3 groups over time, however, significant group differences tracked into adulthood (P < .001 at all stages). A regression model identified pre-pubertal HbA1c as a significant and relevant predictor of metabolic control in young adulthood adjusted for confounders (P < .001). CONCLUSIONS: This survey provides evidence for long-term tracking of metabolic control from childhood until adulthood, suggesting an early focus on metabolic control.
Authors: Natalie Slopen; Alva Tang; Charles A Nelson; Charles H Zeanah; Thomas W McDade; Katie A McLaughlin; Nathan A Fox Journal: Psychosom Med Date: 2019-06 Impact factor: 4.312
Authors: Barbara Bohn; Beate Karges; Christian Vogel; Klaus-Peter Otto; Wolfgang Marg; Sabine E Hofer; Elke Fröhlich-Reiterer; Martin Holder; Michaela Plamper; Martin Wabitsch; Wolfgang Kerner; Reinhard W Holl Journal: PLoS One Date: 2016-08-17 Impact factor: 3.240
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