Major depression is one of the leading causes of disease burden and is prevalent in the general population. Identification of people who are at high risk of developing major depression but currently have no symptoms, which is commonly used in heart disease prevention, may also be useful for primary and secondary interventions of major depression. It is well recognized that major depression is a result of interactions among genetic, biological and psychosocial risk factors. Epidemiological studies in the past decades have identified a number of risk factors for major depression. However, effective strategies for prevention are hindered by lack of evidence about the combined effect of known risk factors.
The proposed study is to develop and validate risk prediction algorithms (or risk estimation equation) for major depression in the Canadian general population. We intend to determine a set of key factors (modifiable and non-modifiable) in valid prediction algorithms for different populations. Based on current exposure to various risk factors, the algorithms could be used for assess short-term and long-term probability of developing major depression among individuals without major depression.
We will use the National Population Health Survey data from 1994/95 to 2008/09 (8 cycles) to develop risk estimate equations for 2-year, 4-year, 6-year and 8-year risk of major depression. We will identify a set of key risk factors which are included in the prediction algorithms. The developed algorithms will be validated internally using the NPHS data.
Principal Investigator: Dr. JianLi Wang
Co- Investigators: Dr. Scott Patten, Dr. Douglas Manuel, Dr. Norbert Schmitz, Heather Gilmour
Funding Source: The Canadian Institutes of Health Research (CIHR)
Project Coordinator: Erin Jones
Heather Gilmour: Senior analyst, Statistics Canada
Dr. Douglas Manuel: Associate Professor, Departments of Family Medicine and of Epidemiology and Community Medicine, University of Ottawa. Senior Scientist, Statistics Canada.