Background: This study evaluated the practicability of the suicide rate reduction target set by the current national suicide prevention policy in Korea, the fifth Master Plan for Suicide Prevention (2023–2027). This policy aims to lower the suicide rate from 26/100,000 in 2021 to 18.2/100,000 by 2027. Methods: We utilized monthly suicide statistics data from 2011 onwards. Using Bayesian regression and Autoregressive Integrated Moving Average (ARIMA) models, we conducted interrupted time series analyses to estimate the effect of the previous policy, the National Action Plan for Suicide Prevention (2018–2022), on suicide rates. We assumed this as the additional suicide reduction expected from the current policy. We generated point predictions and simulations for suicide rates from 2023 to 2027 using Bayesian regression and ARIMA models. Results: The interrupted time series analyses did not reveal a significant reduction in suicides attributable to the previous policy. Point predictions from the two models indicated that the suicide rate would remain approximately 24/100,000 in 2027. Almost all of the simulations of the 2027 suicide rate did not meet the policy target of 18.2/100,000. Conclusion The findings suggest that the Korean government’s suicide rate reduction target for 2027 is likely unattainable based on current trends and the limited effectiveness of previous policies. The objectives of suicide prevention policies should be evidence-based, attainable, and accountable.

Objective: Objective of this study is to evaluate the association between high risk of depression and metabolic diseases such as hypertension, diabetes, and dyslipidemia in Korean cervical cancer patients. Methods: A total of 330 women with cervical cancer were included in this study, using data from the Korea National Health and Nutrition Examination Survey from 2010 to 2021. Participants were categorized into two groups—high risk of depression and non-depression—based on their answers to survey items related to depression. A multivariate logistic regression analysis was used to evaluate the influence of metabolic diseases on high risk of depression in patients with cervical cancer. Results: A total of 78 (23.64%) and 252 (76.36%) women were classified into the high risk of depression and non-depression groups, respectively. In multivariate logistic regression analysis adjusting for age, menopausal status, and smoking status, diabetes was associated with an odds ratio of 2.47 (95% confidence interval: 1.205, 5.071) for high risk of depression in cervical cancer patients. However, among the metabolic diseases, hypertension, and dyslipidemia were not associated with high risk of depression in patients with cervical cancer. Conclusion This study suggests that diabetes may be associated with a increased risk of high risk of depression in cervical cancer patients. Therefore, appropriate treatment of diabetes in cervical cancer patients may contribute to lowering the risk of depression in the future.

Objective: Objective of this study is to evaluate the association between high risk of depression and metabolic diseases such as hypertension, diabetes, and dyslipidemia in Korean cervical cancer patients. Methods: A total of 330 women with cervical cancer were included in this study, using data from the Korea National Health and Nutrition Examination Survey from 2010 to 2021. Participants were categorized into two groups—high risk of depression and non-depression—based on their answers to survey items related to depression. A multivariate logistic regression analysis was used to evaluate the influence of metabolic diseases on high risk of depression in patients with cervical cancer. Results: A total of 78 (23.64%) and 252 (76.36%) women were classified into the high risk of depression and non-depression groups, respectively. In multivariate logistic regression analysis adjusting for age, menopausal status, and smoking status, diabetes was associated with an odds ratio of 2.47 (95% confidence interval: 1.205, 5.071) for high risk of depression in cervical cancer patients. However, among the metabolic diseases, hypertension, and dyslipidemia were not associated with high risk of depression in patients with cervical cancer. Conclusion This study suggests that diabetes may be associated with a increased risk of high risk of depression in cervical cancer patients. Therefore, appropriate treatment of diabetes in cervical cancer patients may contribute to lowering the risk of depression in the future.

Objective: Objective of this study is to evaluate the association between high risk of depression and metabolic diseases such as hypertension, diabetes, and dyslipidemia in Korean cervical cancer patients. Methods: A total of 330 women with cervical cancer were included in this study, using data from the Korea National Health and Nutrition Examination Survey from 2010 to 2021. Participants were categorized into two groups—high risk of depression and non-depression—based on their answers to survey items related to depression. A multivariate logistic regression analysis was used to evaluate the influence of metabolic diseases on high risk of depression in patients with cervical cancer. Results: A total of 78 (23.64%) and 252 (76.36%) women were classified into the high risk of depression and non-depression groups, respectively. In multivariate logistic regression analysis adjusting for age, menopausal status, and smoking status, diabetes was associated with an odds ratio of 2.47 (95% confidence interval: 1.205, 5.071) for high risk of depression in cervical cancer patients. However, among the metabolic diseases, hypertension, and dyslipidemia were not associated with high risk of depression in patients with cervical cancer. Conclusion This study suggests that diabetes may be associated with a increased risk of high risk of depression in cervical cancer patients. Therefore, appropriate treatment of diabetes in cervical cancer patients may contribute to lowering the risk of depression in the future.

Background: This study evaluated the practicability of the suicide rate reduction target set by the current national suicide prevention policy in Korea, the fifth Master Plan for Suicide Prevention (2023–2027). This policy aims to lower the suicide rate from 26/100,000 in 2021 to 18.2/100,000 by 2027. Methods: We utilized monthly suicide statistics data from 2011 onwards. Using Bayesian regression and Autoregressive Integrated Moving Average (ARIMA) models, we conducted interrupted time series analyses to estimate the effect of the previous policy, the National Action Plan for Suicide Prevention (2018–2022), on suicide rates. We assumed this as the additional suicide reduction expected from the current policy. We generated point predictions and simulations for suicide rates from 2023 to 2027 using Bayesian regression and ARIMA models. Results: The interrupted time series analyses did not reveal a significant reduction in suicides attributable to the previous policy. Point predictions from the two models indicated that the suicide rate would remain approximately 24/100,000 in 2027. Almost all of the simulations of the 2027 suicide rate did not meet the policy target of 18.2/100,000. Conclusion The findings suggest that the Korean government’s suicide rate reduction target for 2027 is likely unattainable based on current trends and the limited effectiveness of previous policies. The objectives of suicide prevention policies should be evidence-based, attainable, and accountable.

Background: This study evaluated the practicability of the suicide rate reduction target set by the current national suicide prevention policy in Korea, the fifth Master Plan for Suicide Prevention (2023–2027). This policy aims to lower the suicide rate from 26/100,000 in 2021 to 18.2/100,000 by 2027. Methods: We utilized monthly suicide statistics data from 2011 onwards. Using Bayesian regression and Autoregressive Integrated Moving Average (ARIMA) models, we conducted interrupted time series analyses to estimate the effect of the previous policy, the National Action Plan for Suicide Prevention (2018–2022), on suicide rates. We assumed this as the additional suicide reduction expected from the current policy. We generated point predictions and simulations for suicide rates from 2023 to 2027 using Bayesian regression and ARIMA models. Results: The interrupted time series analyses did not reveal a significant reduction in suicides attributable to the previous policy. Point predictions from the two models indicated that the suicide rate would remain approximately 24/100,000 in 2027. Almost all of the simulations of the 2027 suicide rate did not meet the policy target of 18.2/100,000. Conclusion The findings suggest that the Korean government’s suicide rate reduction target for 2027 is likely unattainable based on current trends and the limited effectiveness of previous policies. The objectives of suicide prevention policies should be evidence-based, attainable, and accountable.