A Cross National Ecological Analysis of Social Determinants in Geriatric Suicide Crises and a Proposal for an Integrated Crisis Response Model

Background Geriatric suicide is a major public health concern, with emergency departments (EDs) often serving as the first point of contact. Current practice focuses on acute stabilization, overlooking the upstream social, economic, and environmental determinants that precipitate these crises. This study aims to analyze these multi-level risk factors and propose a holistic, actionable public health model for emergency medicine. Methods A cross-national ecological analysis was conducted using 2019 data from the WHO Global Health Estimates and the World Bank. The dependent variable was the age-specific suicide rate for adults aged 75–79. Independent variables included the Gini index (income inequality), old-age dependency ratio, digital payment usage among adults 65+ (digital inclusion), and CO2 emissions per capita (proxy for environmental stress). Pearson correlation and multiple linear regression analyses were performed. Results Descriptive statistics revealed significant global variation in all variables. Correlation analysis showed that geriatric suicide rates were positively and significantly correlated with the Gini index (r = 0.58, p < 0.01) and CO2 emissions (r = 0.45, p < 0.05), and negatively correlated with digital payment usage (r = -0.51, p < 0.01). The multiple regression model was significant (F(4, 82) = 18.19, p < 0.001, R² = 0.47), with the Gini index (β = 0.35, p = 0.004) and CO2 emissions (β = 0.28, p = 0.03) emerging as significant predictors of higher suicide rates. Conclusion Geriatric suicide attempts presenting to the ED should be treated as "sentinel health events"—critical indicators of systemic failures in the social, economic, and physical environment. We propose an "Integrated Crisis Response Model" where EDs act as public health nodes. This involves: 1) Enhanced screening for social and environmental risk factors, 2) Initiating "warm handoffs" to community services, and 3) Utilizing anonymized data to advocate for healthier, more age-friendly urban environments.