Spatio-temporal analysis of mental illness and the impact of marginalization-based factors: a case study of Ontario, Canada

Abstract

ABSTRACT Mental illness is a predominant medical condition in Canada. Marginalized groups in the Canadian population such as those with low income, the poorly educated and ethnic minorities are susceptible to mental health disorders. Using mental health-related emergency department visits as an indicator of mental illness cases, we employ a Bayesian spatio-temporal regression model to estimate mental illness risk across the 35 public health units of Ontario, Canada from 2006 to 2017. The association between mental illness and the following marginalization-related factors: material deprivation, residential instability and ethnic concentration is also evaluated. Over the assessed period, the relative risk of mental illness ranged from 0.45 (95% CI: 0.44–0.46) to 3.29 (95% CI: 3.20–3.37). Health units with elevated levels of material deprivation and residential instability were positively associated with increased mental illness risk whilst areas with higher ethnic concentration were linked with lower risk. Findings showed that the temporal trend of risk continuously increased over the 11 year period, with health units in northern Ontario experiencing higher risk compared to southern units. The management of psychiatric disorders presents a significant challenge to the Canadian health-care system. An understanding of the geographic distribution of mental health risk across space and time can be useful for improved policy-making and public health monitoring.