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2 "Il-Su Park"
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Original Articles
Analysis of risk factors affecting suicidal ideation in South Korea by life cycle stage
Ji-Young Hwang, Il-Su Park
Osong Public Health Res Perspect. 2021;12(5):314-323.   Published online October 26, 2021
DOI: https://doi.org/10.24171/j.phrp.2021.0208
  • 5,180 View
  • 134 Download
  • 4 Web of Science
  • 5 Crossref
AbstractAbstract PDF
Objectives
This study analyzed risk factors for suicidal ideation in South Koreans from a life cycle perspective.
Methods
A secondary analysis was conducted of data collected in 2015 as part of the 6th Korea National Health and Nutrition Examination Survey (KNHANES). The participants comprised 5,935 individuals aged 12 years or older. The statistical analysis reflected the complex sampling design of the KNHANES, and the Rao-Scott chi-square test and multiple logistic regression analysis were performed.
Results
The prevalence of suicidal ideation was 5.7% in adolescents, 3.7% in young adults, 5.4% in middle-aged adults, and 7.0% in older adults. Depression and stress were risk factors in every stage of the life cycle. In those aged 12 to 19 years, activity restrictions were significantly associated with suicidal ideation. Education and subjective health status were risk factors in adults aged 20 to 39 years, and education, activity restrictions, and quality of life were the major risk factors in those aged 40 to 64 years. For adults 65 years of age or older, the risk of suicidal ideation was higher among those with inappropriate sleep time.
Conclusion
The risk factors for suicidal ideation were found to be different across stages of the life cycle. This suggests a need for individualized suicide prevention plans and specific government policies that reflect the characteristics of each life cycle stage.

Citations

Citations to this article as recorded by  
  • Association between long working hours and the development of suicidal ideation among female workers: An 8-year population-based study using the Korean Longitudinal Survey of Women & Family (2012–2020)
    Seong-Uk Baek, Yu-Min Lee, Jin-Ha Yoon
    Psychiatry Research.2024; 333: 115731.     CrossRef
  • Prevalence and incidence of suicide, suicidal ideation and self-harm in caregivers of cancer patients: A systematic review and meta-analysis
    Chen Ee Low, Sean Loke, Sounak Rana, Ben Sim, Cyrus Su Hui Ho
    General Hospital Psychiatry.2024; 90: 35.     CrossRef
  • Alcohol Consumption and Quality of Life in Middle-aged Men
    Jeong-Sook Lee
    International Journal of High Risk Behaviors and A.2023;[Epub]     CrossRef
  • Factors Related to Suicidal Ideation by Gender and Age Group in Korean Adults
    Eun Young Kim, Yong Whi Jeong, Jihye Lim, Dae Ryong Kang
    Journal of Korean Medical Science.2023;[Epub]     CrossRef
  • Association between Sleep Duration and Symptoms of Depression Aged between 18 and 49: The Korea National Health and Nutrition Examination Survey (KNHANES Ⅶ) from 2016 to 2018
    Sung-Yong Choi, Ji-Eun Han, Jiae Choi, Minjung Park, Soo-Hyun Sung, Angela Dong-Min Sung
    Healthcare.2022; 10(11): 2324.     CrossRef
Developing the High-Risk Drinking Scorecard Model in Korea
Jun-Tae Han, Il-Su Park, Suk-Bok Kang, Byeong-Gyu Seo
Osong Public Health Res Perspect. 2018;9(5):231-239.   Published online October 31, 2018
DOI: https://doi.org/10.24171/j.phrp.2018.9.5.04
  • 16,572 View
  • 103 Download
  • 3 Crossref
AbstractAbstract PDF
Objectives

This study aimed to develop a high-risk drinking scorecard using cross-sectional data from the 2014 Korea Community Health Survey.

Methods

Data were collected from records for 149,592 subjects who had participated in the Korea Community Health Survey conducted from 2014. The scorecard model was developed using data mining, a scorecard and points to double the odds approach for weighted multiple logistic regression.

Results

This study found that there were many major influencing factors for high-risk drinkers which included gender, age, educational level, occupation, whether they received health check-ups, depressive symptoms, over-moderate physical activity, mental stress, smoking status, obese status, and regular breakfast. Men in their thirties to fifties had a high risk of being a drinker and the risks in office workers and sales workers were high. Those individuals who were current smokers had a higher risk of drinking. In the scorecard results, the highest score range was observed for gender, age, educational level, and smoking status, suggesting that these were the most important risk factors.

Conclusion

A credit risk scorecard system can be applied to quantify the scoring method, not only to help the medical service provider to understand the meaning, but also to help the general public to understand the danger of high-risk drinking more easily.

Citations

Citations to this article as recorded by  
  • Risk score models for urinary tract infection hospitalization
    Nasrin Alizadeh, Kimia Vahdat, Sara Shashaani, Julie L. Swann, Osman Y. Özaltιn, Guillermo Pineda Villavicencio
    PLOS ONE.2024; 19(6): e0290215.     CrossRef
  • A Study on ML-Based Sleep Score Model Using Lifelog Data
    Jiyong Kim, Minseo Park
    Applied Sciences.2023; 13(2): 1043.     CrossRef
  • A Simple-to-Use Score for Identifying Individuals at High Risk of Denosumab-Associated Hypocalcemia in Postmenopausal Osteoporosis: A Real-World Cohort Study
    Kyoung Jin Kim, Namki Hong, Seunghyun Lee, Miryung Kim, Yumie Rhee
    Calcified Tissue International.2020; 107(6): 567.     CrossRef

PHRP : Osong Public Health and Research Perspectives