J Korean Neuropsychiatr Assoc.  2024 Nov;63(4):237-245. 10.4306/jknpa.2024.63.4.237.

Changes in Suicide Rate Trend After Implementation of Suicide Prevention Policy: An Interrupted Time Series Study on the Fifth Master Plan for Suicide Prevention

• Ryu S
• Baek SH
• Jhon M
• Kim H
• Lee JY
• Kim JM
• Kim SW

• KMID: 2561748
• DOI: http://doi.org/10.4306/jknpa.2024.63.4.237

Abstract

Objectives
This study examined the shifts in the suicide trends in Korea during the initial phase of the Fifth Master Plan for Suicide Prevention, using interrupted time series analyses.
Methods
Interrupted time series analyses were performed using the monthly suicide data from January 2011 to April 2024. Quasi-Poisson regression models were applied to evaluate the changes in the level and slope of the suicide trend before and after policy implementation. The Autoregressive Integrated Moving Average (ARIMA) and Prophet models were used to compare the actual and predicted counterfactual numbers of suicides during the policy period.
Results
The quasi-Poisson regression model revealed a significant change in the trend of suicides among men, with an increasing slope during the policy period. For total suicides, the ARIMA and Prophet models suggested that the actual number of suicides was significantly higher than the counterfactual number during the policy period, with excess suicides averaging between 113 and 150 per month. The actual number of suicides among men was significantly higher than the counterfactual number during the policy period, with excess suicides averaging between 86 and 92 per month. No significant changes in the suicide trends among women were observed.
Conclusion
These findings suggest that the initial effects of the Fifth Master Plan for Suicide Prevention were inadequate to curb the rising suicide trends, particularly among men. This study underscores the need for timely policy responses to reverse the current increasing trend in suicides, with particular focus on the male population.

Keyword

Suicide; Policy; Interrupted time series analysis