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
Bibliographic Data
| ID | 22032063 |
|---|---|
| Authors | Abu Yousuf Md Abdullah (0000-0001-8641-990X, University of Waterloo, corresponding author), Jane Law (0000-0001-6259-9037, University of Waterloo) |
| Year | 2024 |
| Volume | 13 |
| Issue | 3 |
| Pages | 75 |
| Publication date | 2024-02-28 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | ISPRS International Journal of Geo-Information (JOURNAL) |
| Journal identifiers | ISSN: 2220-9964 • E-ISSN: 2220-9964 |
| Publisher | MDPI AG (PUBLISHER • IT) |
| DOI | 10.3390/ijgi13030075 |
| OpenAlex | W4392232578 |
| Language | EN |
| Citations received | 1 |
| References cited | 56 |
Mental health disorder risks of young and old age groups hold considerable importance for understanding present and future risk burdens. However, assessing mental health risks is significantly constrained by the influence of shared and age group-specific spatial processes and risk factors. Therefore, this study employed Bayesian shared component spatial modeling (BSCSM) to analyze mental health disorder data obtained from young (20–44 years) and old (65+ years) age groups in Toronto. BSCSM was employed to model the shared and age group-specific disorder risk and to identify hotspot areas. The unmeasured covariates, overdispersion, and latent spatial processes were adjusted using spatial and non-spatial random effect terms. The findings from BSCSM were finally compared with non-shared component modeling approaches. The results suggest that over 60% of variations in mental health disorder risk for both age groups could be explained by the shared component. The high-risk neighborhoods were mainly localized in southern and north-central Toronto for the young and old age groups. Deviance information criterion values suggested that models from BSCSM outperformed non-BSCSM models. BSCSM risk maps were also better at identifying high-risk areas. This work demonstrated that both shared and age group-specific risks are essential for assessing mental health disorder risk and devising targeted interventions
Geography · Mental health · Psychiatry · Sociology · Demography · Health disparities and outcomes · Medicine · Psychology · Spatial and Panel Data Analysis · Urban Transport and Accessibility · Gerontology
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| Citations per year | 1 |
|---|---|
| Citation span | 2025 - 2025 (1) |
| Highly cited | No |