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Diabetic Cohort (DC)
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Sample details

The DC was established to investigate the determinants of complications in individuals with type 2 diabetes and to examine the roles of genetic, physiological, and lifestyle factors in the development of complications in these individuals. Participants include adult Singaporeans and permanent residents (aged 21 years and above) with physician-diagnosed type 2 diabetes. Individuals with mental illness, clinically-obvious non-diabetic kidney disease (such as polycystic kidney disease), type 1 diabetes, or diabetes mellitus resulting from endocrinopathies were not included. Data have been collected at three different timepoints: baseline (2004-2010, DC_T1); first follow-up (2010-2016, DC_T2); and second follow-up (2016-2021, DC_T3). The mean age of participants at baseline was 59.7 years, and 50.8% of participants were men. The ethnic composition of the sample was 59.3% Chinese, 22.7% Malay, and 17.3% Indian.

Study design
Cohort - clinical

Number of participants at first data collection

14,033 (participants)

Age at first data collection

≥ 21 years (participants)

Participant year of birth

Varied (participants)

Participant sex
All

Representative sample at baseline?
No

Sample features

Adults
Diabetes patients
Dataset details

Country

Singapore

Year of first data collection

2004

Primary Institutions

National University Health System (NUHS)

National University of Singapore (NUS)

Links

blog.nus.edu.sg/sphs/population-studies/diabetic-cohort-dc/

Funders

Biomedical Research Council

Ministry of Health

National Medical Research Council (NMRC)

National University Health System (NUHS)

National University of Singapore (NUS)

Ongoing?
Yes

Data types collected

mentalHealthData
dataLinkage
Quantitative data collection
  • Computer, paper or task testing (e.g. cognitive testing, theory of mind doll task, attention computer tasks)
  • Interview – face-to-face
  • Interview – phone
  • Physical or biological assessment (e.g. blood, saliva, gait, grip strength, anthropometry)
  • Secondary data
  • Self-completed questionnaire – online
Qualitative data collection
  • None
Neuroimaging data collection
  • None
Linked or secondary data
  • Healthcare data
Features

Engagement

  • Community engagement
  • Keywords

    Anthropometry
    Biological samples/biospecimens
    Diabetes
    Diet and nutrition
    Disease progression
    Environmental factors
    Lifestyle factors
    Public health

    Consortia and dataset groups

    PRECISE-SG100K
    Singapore Population Health Studies (SPHS)
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