Emily Hazell
Exploring Individual and Contextual Influences on Self-Perceived Mental Health of Foreign-Born Populations within the Toronto CMA, 2007-2010 © 2012
The health of Canadian immigrants is an important topic to investigate as it provides a unique perspective into the disparities present in population health. This cross-sectional study adds to the growing literature exploring immigrant health disparities within a Canadian context, in particular healthy immigrant effect whereby as residency time increases, health is thought to deteriorate; and ethnic density effect that postulates an association between highly dense same group neighbourhoods and relative health outcomes. Using data derived from the Canadian Community Health Survey (CCHS) and 2006 Census, as well as spatially derived Census-based variables such as ethnic density, this study examines the impact of individual and contextual influences have on the mental health status of foreign-born populations within the Toronto CMA. Spatial variance in poor or fair self perceived mental health status of immigrants was depicted using two non-parametric approaches of cluster detection, including kernel density estimation and SaTScan. High risk clusters of mental illness were found in suburban communities, with lower risk regions found in downtown Toronto and rural parts of the CMA. Using logistic regression analysis, individual factors such as age and body mass index were found to be determinants of poor or fair mental health status of immigrants in conjunction with contextual influences such as ethnic density. No inferences could be made in regard to healthy immigrant effect, as no concrete evidence was found to suggest that increased residency time in Canada determined a higher prevalence of mental illness. For ethnic density effect, future studies should adopt both quantitative measures of ethnic density using spatial analysis and qualitative approaches such self-perceived ethnic density to account for regional disparities in mental health among foreign-born populations.