BACKGROUND AND AIM:Suicide is a serious preventable problem. The study aimed to identify the incidence and provincial factors associated with suicide rate in 2016-2020.
METHOD:The researcher performed an ecological study using secondary data from the national databases. Moreover, univariate spatial data analysis was used to identify geographical hot spots, and Poisson regression model was used to determine the factors associated with completed suicide.
RESULTS:The results showed that mean suicide incidence increased from 6.62 (SD 2.87) to 7.99 (SD 4.54) cases per 100,000 population. Results from Moran's I analysis, the high incidence of suicide was clustered in the North, whereas low incidence of suicide was clustered in the Central and Deep South. Factors associated with increased provincial suicide incidence were higher proportion of patients with stroke (Adj. IRR 1.07, 95%CI 1.03-1.11), higher proportion of patients with major depressive disorder (Adj. IRR 1.06, 95%CI 1.02-1.11), higher proportion of patients with alcohol dependency (Adj. IRR 1.01, 95%CI 1.00-1.02), and higher proportion of forest area (Adj. IRR 1.06, 95%CI 1.03-1.09). Preventive factors against provincial suicide incidence were higher proportion of young population (Adj. IRR 0.000003, 95%CI 0.00-0.05), higher proportion of the working-age population (Adj. IRR 0.08, 95%CI 0.01-0.51), higher proportion of patients with CVD (Adj. IRR 0.97, 95%CI 0.94-0.99), higher proportion of patients with schizophrenia (Adj. IRR 0.97, 95%CI 0.94-0.99), and higher hospital-to-population ratio (Adj. IRR 0.97, 95%CI 0.95-0.99).
CONCLUSIONS:The study found that provincial factors are linked to completed suicide rates. Biological factors like youth and working-age proportions, along with psychopathological factors such as stroke, alcohol dependency, CVD, and schizophrenia proportions, were associated with higher rates. Conversely, no significant correlation was found between provincial psychosocial factors and completed suicide rates. However, a notable link was observed between societal factors like the proportion of forest area and increased completed suicide rates.

Keywords: Neurologic and mental health outcomes, Big data, Epidemiology, Mental health outcomes