Christine W Hockett1, Pradeep A Praveen2, Toan C Ong3, Anandakumar Amutha4, Scott P Isom5, Elizabeth T Jensen6, Ralph B D'Agostino5, Richard F Hamman1, Elizabeth J Mayer-Davis7, Jean M Lawrence8, Catherine Pihoker9, Michael G Kahn3, Viswanathan Mohan4, Nikhil Tandon2, Dana Dabelea1. 1. Lifecourse Epidemiology of Adiposity and Diabetes Center, Colorado School of Public Health, University of Colorado Denver, Aurora, Colorado. 2. Department of Endocrinology & Metabolism, All India Institute of Medical Sciences, New Delhi, India. 3. Department of Pediatrics, University of Colorado, Aurora, Colorado. 4. Dr. Mohan's Diabetes Specialties Centre and Madras Diabetes Research Foundation, Chennai, India. 5. Department of Biostatistics and Bioinformatics, Wake Forest School of Medicine, Winston-Salem, North Carolina. 6. Department of Epidemiology, Wake Forest School of Medicine, Winston-Salem, North Carolina. 7. Department of Nutrition and Medicine, University of North Carolina, Chapel Hill, North Carolina. 8. Department of Research & Evaluation, Kaiser Permanente Southern California, Pasadena, California. 9. Department of Pediatrics, University of Washington, Seattle, Washington.
Abstract
BACKGROUND: Over the last decades, diabetes in youth has increased in both India and the United States, along with the burden of long-term complications and healthcare costs. However, there are limited standardized population-based data in contemporary youth cohorts for comparison of clinical and demographic characteristics of diabetes for both type 1 (T1D) and type 2 (T2D). METHODS: In partnership, we harmonized demographic and clinical data from the SEARCH for Diabetes in Youth (SEARCH) registry in the United States and the Registry of People with Diabetes with Youth Age at Onset (YDR) in India to the structure and terminology of the Observational Medical Outcomes Partnership Common Data Model. Data were from youth with T1D and T2D, aged <20 years and newly diagnosed between 2006 and 2010. We compared key characteristics across registries using χ2 tests and t-tests. RESULTS: In total, there were 9650 youth with T1D and 2406 youth with T2D from 2006 to 2012. SEARCH youth were diagnosed at younger ages than YDR youth for T1D and T2D (10.0 vs 10.5 years, P < .001 and 14.7 vs 16.1 years, P < .001, respectively). For T2D, SEARCH had a higher proportion of females and significantly lower proportion of youth of high socioeconomic status compared to YDR. For T1D and T2D, SEARCH youth had higher BMI, lower blood pressure, and lower A1c compared to YDR youth. CONCLUSIONS: These data offer insights into the demographic and clinical characteristics of diabetes in youth across the two countries. Further research is needed to better understand why these differences exist.
BACKGROUND: Over the last decades, diabetes in youth has increased in both India and the United States, along with the burden of long-term complications and healthcare costs. However, there are limited standardized population-based data in contemporary youth cohorts for comparison of clinical and demographic characteristics of diabetes for both type 1 (T1D) and type 2 (T2D). METHODS: In partnership, we harmonized demographic and clinical data from the SEARCH for Diabetes in Youth (SEARCH) registry in the United States and the Registry of People with Diabetes with Youth Age at Onset (YDR) in India to the structure and terminology of the Observational Medical Outcomes Partnership Common Data Model. Data were from youth with T1D and T2D, aged <20 years and newly diagnosed between 2006 and 2010. We compared key characteristics across registries using χ2 tests and t-tests. RESULTS: In total, there were 9650 youth with T1D and 2406 youth with T2D from 2006 to 2012. SEARCH youth were diagnosed at younger ages than YDR youth for T1D and T2D (10.0 vs 10.5 years, P < .001 and 14.7 vs 16.1 years, P < .001, respectively). For T2D, SEARCH had a higher proportion of females and significantly lower proportion of youth of high socioeconomic status compared to YDR. For T1D and T2D, SEARCH youth had higher BMI, lower blood pressure, and lower A1c compared to YDR youth. CONCLUSIONS: These data offer insights into the demographic and clinical characteristics of diabetes in youth across the two countries. Further research is needed to better understand why these differences exist.
Authors: Juliana C N Chan; Vasanti Malik; Weiping Jia; Takashi Kadowaki; Chittaranjan S Yajnik; Kun-Ho Yoon; Frank B Hu Journal: JAMA Date: 2009-05-27 Impact factor: 56.272
Authors: Christine L Chan; Kim McFann; Lindsey Newnes; Kristen J Nadeau; Philip S Zeitler; Megan Kelsey Journal: Pediatr Diabetes Date: 2014-03-17 Impact factor: 4.866
Authors: Beatriz L Rodriguez; Dana Dabelea; Angela D Liese; Wilfred Fujimoto; Beth Waitzfelder; Lenna Liu; Ronny Bell; Jennifer Talton; Beverly M Snively; Ann Kershnar; Elaine Urbina; Stephen Daniels; Giuseppina Imperatore Journal: J Pediatr Date: 2010-04-14 Impact factor: 4.406
Authors: Mercedes de Onis; Adelheid W Onyango; Elaine Borghi; Amani Siyam; Chizuru Nishida; Jonathan Siekmann Journal: Bull World Health Organ Date: 2007-09 Impact factor: 9.408
Authors: William C Hsu; Maria Rosario G Araneta; Alka M Kanaya; Jane L Chiang; Wilfred Fujimoto Journal: Diabetes Care Date: 2015-01 Impact factor: 19.112
Authors: Richard F Hamman; Ronny A Bell; Dana Dabelea; Ralph B D'Agostino; Lawrence Dolan; Giuseppina Imperatore; Jean M Lawrence; Barbara Linder; Santica M Marcovina; Elizabeth J Mayer-Davis; Catherine Pihoker; Beatriz L Rodriguez; Sharon Saydah Journal: Diabetes Care Date: 2014-12 Impact factor: 19.112