Elizabeth T Jensen1, Dana A Dabelea2, Pradeep A Praveen3, Anandakumar Amutha4, Christine W Hockett2, Scott P Isom5, Toan C Ong6, Viswanathan Mohan4, Ralph D'Agostino5, Michael G Kahn6, Richard F Hamman2, Paul Wadwa6, Lawrence Dolan7, Jean M Lawrence8, S V Madhu9, Reshmi Chhokar3, Komal Goel3, Nikhil Tandon3, Elizabeth Mayer-Davis10. 1. Department of Epidemiology and Prevention, Wake Forest School of Medicine, Winston-Salem, NC, USA. 2. Department of Epidemiology, Colorado School of Public Health, University of Colorado Denver, Aurora, CO, USA. 3. Department of Endocrinology, Metabolism and Diabetes, All India Institute of Medical Sciences, New Delhi, India. 4. Dr. Mohan's Diabetes Specialties Centre and Madras Diabetes Research Foundation, Chennai, India. 5. Department of Biostatistics and Data Sciences, Wake Forest School of Medicine, Winston-Salem, NC, USA. 6. Department of Pediatrics, University of Colorado, Aurora, CO, USA. 7. Department of Pediatrics, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA. 8. Department of Research & Evaluation, Kaiser Permanente Southern California, Pasadena, CA, USA. 9. Department of Endocrinology, Centre for Diabetes, Endocrinology and Metabolism, University College of Medical Science, GTB Hospital, Delhi, India. 10. Department of Nutrition and Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
Abstract
OBJECTIVE: Incidence of youth-onset diabetes in India has not been well described. Comparison of incidence, across diabetes registries, has the potential to inform hypotheses for risk factors. We sought to compare the incidence of diabetes in the U.S.-based registry of youth onset diabetes (SEARCH) to the Registry of Diabetes with Young Age at Onset (YDR-Chennai and New Delhi regions) in India. METHODS: We harmonized data from both SEARCH and YDR to the Observational Medical Outcomes Partnership (OMOP) Common Data Model. Data were from youth registered with incident diabetes (2006-2012). Denominators were from census and membership data. We calculated diabetes incidence by averaging the total cases across the entire follow-up period and dividing this by the estimated census population corresponding to the source population for case ascertainment. Incidence was calculated for each of the registries and compared by type and within age and sex categories using a 2-sided, skew-corrected inverted score test. RESULTS: Incidence of type 1 was higher in SEARCH (21.2 cases/100 000 [95% CI: 19.9, 22.5]) than YDR (4.9 cases/100 000 [95% CI: 4.3, 5.6]). Incidence of type 2 diabetes was also higher in SEARCH (5.9 cases/100 000 [95% CI: 5.3, 6.6] in SEARCH vs 0.5/cases/100 000 [95% CI: 0.3, 0.7] in YDR). The age distribution of incident type 1 diabetes cases was similar across registries, whereas type 2 diabetes incidence was higher at an earlier age in SEARCH. Sex differences existed in SEARCH only, with a higher rate of type 2 diabetes among females. CONCLUSION: The incidence of youth-onset type 1 and 2 diabetes was significantly different between registries. Additional data are needed to elucidate whether the differences observed represent diagnostic delay, differences in genetic susceptibility, or differences in distribution of risk factors.
OBJECTIVE: Incidence of youth-onset diabetes in India has not been well described. Comparison of incidence, across diabetes registries, has the potential to inform hypotheses for risk factors. We sought to compare the incidence of diabetes in the U.S.-based registry of youth onset diabetes (SEARCH) to the Registry of Diabetes with Young Age at Onset (YDR-Chennai and New Delhi regions) in India. METHODS: We harmonized data from both SEARCH and YDR to the Observational Medical Outcomes Partnership (OMOP) Common Data Model. Data were from youth registered with incident diabetes (2006-2012). Denominators were from census and membership data. We calculated diabetes incidence by averaging the total cases across the entire follow-up period and dividing this by the estimated census population corresponding to the source population for case ascertainment. Incidence was calculated for each of the registries and compared by type and within age and sex categories using a 2-sided, skew-corrected inverted score test. RESULTS: Incidence of type 1 was higher in SEARCH (21.2 cases/100 000 [95% CI: 19.9, 22.5]) than YDR (4.9 cases/100 000 [95% CI: 4.3, 5.6]). Incidence of type 2 diabetes was also higher in SEARCH (5.9 cases/100 000 [95% CI: 5.3, 6.6] in SEARCH vs 0.5/cases/100 000 [95% CI: 0.3, 0.7] in YDR). The age distribution of incident type 1 diabetes cases was similar across registries, whereas type 2 diabetes incidence was higher at an earlier age in SEARCH. Sex differences existed in SEARCH only, with a higher rate of type 2 diabetes among females. CONCLUSION: The incidence of youth-onset type 1 and 2 diabetes was significantly different between registries. Additional data are needed to elucidate whether the differences observed represent diagnostic delay, differences in genetic susceptibility, or differences in distribution of risk factors.
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