Please use this identifier to cite or link to this item: https://doi.org/10.1136/bmjopen-2019-036443
Title: Cohort profile: the Singapore diabetic cohort study
Authors: Luo, M.
Tan, L.W.L. 
Sim, X. 
Ng, M.K.H. 
Van Dam, R. 
Tai, E.S. 
Chia, K.S. 
Tang, W.E.
Seah, D.E.
Venkataraman, K. 
Keywords: diabetes & endocrinology
diabetic nephropathy & vascular disease
diabetic neuropathy
diabetic retinopathy
epidemiology
Issue Date: 2020
Publisher: NLM (Medline)
Citation: Luo, M., Tan, L.W.L., Sim, X., Ng, M.K.H., Van Dam, R., Tai, E.S., Chia, K.S., Tang, W.E., Seah, D.E., Venkataraman, K. (2020). Cohort profile: the Singapore diabetic cohort study. BMJ open 10 (5) : e036443. ScholarBank@NUS Repository. https://doi.org/10.1136/bmjopen-2019-036443
Rights: Attribution-NonCommercial 4.0 International
Abstract: PURPOSE: The diabetic cohort (DC) was set up to study the determinants of complications in individuals with type 2 diabetes and examine the role of genetic, physiological and lifestyle factors in the development of complications in these individuals. PARTICIPANTS: A total of 14?033 adult participants with type 2 diabetes were recruited from multiple public sector polyclinics and hospital outpatient clinics in Singapore between November 2004 and November 2010. The first round of follow-up was conducted for 4131 participants between 2012 and 2016; the second round of follow-up started in 2016 and is expected to end in 2021. A questionnaire survey, physical assessments, blood and urine sample collection were conducted at recruitment and each follow-up visit. The data set also includes genetic data and linkage to medical and administrative records for recruited participants. FINDINGS TO DATE: Data from the cohort have been used to identify determinants of diabetes and related complications. The longitudinal data of medical records have been used to analyse diabetes control over time and its related outcomes. The cohort has also contributed to the identification of genetic loci associated with type 2 diabetes and diabetic kidney disease in collaboration with other large cohort studies. About 25 scientific papers based on the DC data have been published up to May 2019. FUTURE PLANS: The rich data in DC can be used for various types of research to study disease-related complications in patients with type 2 diabetes. We plan to further investigate disease progression and new biomarkers for common diabetic complications, including diabetic kidney disease and diabetic neuropathy. © Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.
Source Title: BMJ open
URI: https://scholarbank.nus.edu.sg/handle/10635/196146
ISSN: 2044-6055
DOI: 10.1136/bmjopen-2019-036443
Rights: Attribution-NonCommercial 4.0 International
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