The QTR was initiated as the main part of the Chinese National Twin Registry in 1998 and aimed to primarily recruit twins born in the Qingdao region in China to estimate genetic and environmental components in non-communicable diseases. By 2005, a total of 10,655 twin pairs had been recruited. Since then new twin cohorts have been sampled, such as The Adolescent Twin Cohort, which aims to explore determinants of metabolic disorders and health behaviours during puberty and young adulthood. The adolescent twins were born between 1990 and 1996 and recruited from 2000. The study includes 600 twin pairs (1,200 individuals), and data collection began in 2006 when the twins were 10-16 years old. Finally, an Adult Twin Survey was established in 2001, where a total of 695 pairs of adult twins (MZ = 405, DZ = 290) with a mean age of 37 years were recruited in this study. Anthropometric measurements of metabolic phenotypes were collected from these twins in 2001, and were followed up in 2004 and 2008.
Study design
Cohort - twin, Registry
Number of participants at first data collection
1,200 (adolescent twin participants)
1,390 (adult twin participants)
21,310 (original QTR participants, as of 2005)
Age at first data collection
10 - 16 years (adolescent twin participants)
≥ 18 years (adult twin participants)
Varied (original QTR participants)
Participant year of birth
1990 – 1996 (adolescent twin participants)
Varied (adult twin participants)
Varied (original QTR participants)
Participant sex
All
Representative sample at baseline?
No
Sample features
Country
Year of first data collection
2006 (adolescent twin participants)
2001 (adult twin participants)
1998 (original QTR participants)
Primary Institutions
Chinese Center for Disease Control and Prevention (中国疾病预防控制中心, CCDC)
Profile paper DOI
Funders
China Medical Board (CMB)
European Association for the Study of Diabetes (EASD)
National Institutes of Health (NIH)
National Natural Science Foundation of China (国家自然科学基金委员会, NSFC)
Novo Nordisk Foundation
Ongoing?
Yes
Data types collected
Engagement
Keywords
Consortia and dataset groups