Cohort Consortium Members
Melbourne Collaborative Cohort Study
Lead Contacts and/or Principal Investigators (PIs):
- Graham Gilles, Ph.D.
- Gianluca Severi, Ph.D.
- Dallas English, Ph.D.
Cancer Epidemiology Centre, Cancer Council Victoria, Australia
Centre for MEGA Epidemiology, The University of Melbourne, Australia
Funded Since: 1989
Funding Source: Vic Health, Cancer Council Victoria, and Australian National Health and Medical Research Council (NH&MRC)
Year(s) of Enrollment: 1990-1994
The Melbourne Collaborative Cohort Study is a longitudinal study established in the 1990s by Cancer Council Victoria to investigate prospectively the role of diet and other lifestyle factors in cancer.
Between 1990 and 1994, 41,500 people (24,500 women and 17,000 men) aged 40 to 69 were recruited into the study. Approximately one third of participants are southern European migrants to Australia, who were deliberately over-sampled to extend the range of data on lifestyle exposures and to increase genetic variation. At baseline, lifestyle exposure information, including dietary intake, was collected in a face-to-face interview. Physical measurements and blood pressure were also taken. A sample of blood was drawn and stored for analysis of DNA and other molecules of interest.
Follow-up was conducted by mailed questionnaire and telephone to update lifestyle exposures and self-reports of non-cancer, non-fatal health events at 3 to 4 years after baseline. During 2003-2006, approximately 27,000 cohort participants attended the study centre to repeat the baseline measures and health survey. Follow-up is continuing.
The study’s main focus has been on identifying risk factors for cancer and other chronic diseases, such as type 2 diabetes, cardiovascular disease, eye disease, and arthritis. Through data collected from this contemporary large cohort study, the investigators are studying the determinants of chronic disease, with the aim of developing prediction tools applicable to the current Australian population. Results from this study will allow future patterns of chronic disease to be accurately forecasted, which in turn permits preventive strategies to be used in a more effective manner.