Caron is associate professor of psychiatry at McGill University and researcher at the Research center of the Douglas Mental Health university Institute. He currently leads the team of Canadian Institute of Health Research (CIHR) in Social and Psychiatric Epidemiology. He is also associate researcher at the Institute of Public Health of the University of Montreal and at the Instituto de Saude Colletiva of the Federal University of Bahia in Brazil.


The aim of this study is to identify predictors of well-being, a positive indicator of mental health. We used data from the Montreal Epidemiological Catchment Area Study, a longitudinal study that focuses on the mental health and well-being of residents in the southwest region of Montreal. The study recruited a randomly selected sample of 2,433 individuals aged 15-65 at baseline. Of them, 1,303 were re-interviewed four years later. Well-being was measured with Personal Well-being Index (Cummins, 2003). Direct interviews gathered self-reported data on: socio-demographics, life events, stress and coping abilities, social support, perceptions of neighbourhoods, working status and income, mental disorders, psychiatric family history and mental health services utilization. Social and built features of environment were determined using Geographic Information System. We employed hierarchical linear regression to identify significant independent predictors of well-being improvement overtime, among the aforementioned baseline variables. We first used forward selection procedure to identify significant variable blocks – groups of variables that had significant overall effects on well-being. We then used backward deletion procedure to eliminate non-significant individual variables. The final model explained 41% of the variance of well-being. Variables from eight blocks were found to be significant predictors of well-being, including socio-demographics, income, stress and coping, social support, mental health status, satisfaction with precise life domains, satisfaction with the physical state, density of the vegetation in the neighbourhood, and average property values in the neighbourhood. Better understanding predictors of well-being will enable the development of more effective mental health promotion programs.