Background: Korea had the highest suicide rate among OECD countries for the 10 years leading up to 2016; however, the suicide rate in Korea has declined since 2010, after policy-driven interventions were implemented. Methods: Suicide rates from all of the 229 cities, counties, and districts in Korea were reliably estimated from the period 2010 to 2017, and data were examined by Stata 14.0 and M-plus to identify regional suicide rate change patterns by latent growth modeling. The dependent variable is the suicide rate, and independent variables as characteristics of the various districts are the region (cities, counties, and autonomous districts), proportion of elderly residents, financial independence rate, establishment of mental health and welfare centers, and number of social welfare facilities. Results: Three suicide rate change patterns were identified: 'average', 'precipitous drop', and 'high level'. Two of the three patterns exhibit features that are markedly different to the national data as a whole, and the three patterns appear across the 229 cities, counties, and districts of Korea. Some of the determinant factors have been postulated here. While a high proportion of elderly residents in a given area is a significant indicator that the suicide rate will increase, having a large elderly population in combination with an increased number of social welfare facilities centers appeared to show a discrete pattern of suicide rate reduction when compared with average national data. Conclusions: Policy-driven interventions should be planned and implemented by central and local governments in conjunction, by considering regional characteristics to decrease local suicide rates more effectively.
Keywords: growth mixture model; latent growth model; multinomial logistic analysis; suicide in Korea; typology study.