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

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.

Bayesian Shared Component Spatial Modeling for Assessing the Shared and Age Group-Specific Mental Health Disorder Risk of Young and Old Age Groups: A Case Study of Toronto Neighborhoods, Canada

“…For example, material deprivation is a socioeconomic risk factor that affects both the young and old age groups [3,61,62]. Furthermore, past studies have reported that material deprivation varied geographically in Ontario, with more deprived areas experiencing elevated risks of mental illness and psychotic disorders [41,62]. These findings suggest that the risk factors, which had spatially varied amongst the neighborhoods in Toronto, could have potentially influenced the variations in the shared and age group-specific risks amongst the neighborhoods.…”

“…Finally, it addresses any data sparsity issues caused by a small population or low counts of cases [8,28,34]. Although various spatial risk assessment techniques have been employed in the past, such as the spatial-point pattern analysis [35], spatial error and lag models [36,37], geographically weighted regression [38,39], and Bayesian geoadditive quantile [40] and Poisson regression techniques [10,41,42], the use of joint models has been quite limited in mental health studies [8].…”

Association between maternal marginalization and infants born with congenital heart disease in Ontario Canada

“…Despite this, in Canada, the majority of those living in housing below standards are more likely to be from the lowest income groups, unemployed adults, new immigrants, and those belonging to a visible minority group [66]. Furthermore, with inflated housing prices, it forces these underprivileged persons to relocate often which can impair adequate prenatal care and perpetuate social deprivation [67]. This indicates that other SES indicators such as race, income, and employment are potential mediators between residential stability and adverse health outcomes [68].…”

Psychosis Prevalence in London Neighbourhoods; a Case Study in Spatial Confounding

“…Other evidence on area psychosis variations points to area deprivation as raising psychosis risk [9,10], and similarly for area social fragmentation [11,12]. These area characteristics, broadly denoted as marginalization indicators [13], have been associated with both socio-economic causation, and residential social drift interpretations of psychotic illness [14]. Social fragmentation may act as a contextual in uence as it "re ects potential lack of close/intimate relationships and transient residence in the area" [15].…”