Next Article in Journal
Epidemiological Analysis of Diabetes-Related Hospitalization in Poland before and during the COVID-19 Pandemic, 2014–2020
Previous Article in Journal
Is Working from Home during COVID-19 Associated with Increased Sports Participation? Contexts of Sports, Sports Location and Socioeconomic Inequality
Previous Article in Special Issue
The Impact of Transitions in Caregiving Status on Depressive Symptoms among Older Family Caregivers: Findings from the Korean Longitudinal Study of Aging
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Factors Related to Suicidal Ideation and Prediction of High-Risk Groups among Youngest-Old Adults in South Korea

1
Department of Nursing, Chungbuk National University, Cheongju 28644, Korea
2
College of Nursing, Gyeongsang National University, Jinju 52727, Korea
3
Institute of Health Sciences, Gyeongsang National University, Jinju 52727, Korea
*
Author to whom correspondence should be addressed.
Int. J. Environ. Res. Public Health 2022, 19(16), 10028; https://doi.org/10.3390/ijerph191610028
Submission received: 8 June 2022 / Revised: 6 August 2022 / Accepted: 12 August 2022 / Published: 14 August 2022
(This article belongs to the Special Issue Suicide and Depression in the Elderly)

Abstract

:
(1) Background: The suicide of older adults shows different factors between the youngest-old adults and the old-old adults. This study aimed to identify factors predicting suicidal ideation among youngest-old adults (ages 65 to 74 years) and predict high-risk groups’ characteristics. (2) Methods: The subjects of this study were 970 youngest-old adults who participated in the Korean National Health and Nutrition Examination Survey (KNHANES VIII Year 1, 2019). Logistic regression analysis identified factors related to suicidal ideation, and decision tree analysis identified combined characteristics among high-risk groups. Data were analyzed using SPSS 27.0. (3) Results: Suicidal ideation became more common among those with relatively lower income levels (OR = 1.48, 95% CI = 1.04–2.12), those whom had experienced depression (OR = 9.28, 95% CI = 4.57–18.84), those with relatively higher stress levels (OR = 2.42, 95% CI = 1.11–5.28), and those reporting a relatively worse perceived health (OR = 1.88, 95% CI = 1.23–3.11). Complex characteristics that combined depression, low personal income level, and low perceived health predicted a high risk of suicidal ideation (64.6%, p < 0.05). (4) Conclusions: The findings indicate that this high-risk group should be prioritized when developing suicide prevention strategies.

1. Introduction

Old age may limit physical and mental abilities, affect social and economic activities, and be accompanied by chronic disorders [1]. These characteristics may threaten older adults’ quality of life and possibly trigger depression and even suicidal ideation [2]. Although suicide rates vary from country to country, suicide among older adults is a global public health issue, as they commit suicide at higher rates than other age groups [3,4]. Notably, South Korea’s suicide rate has ranked high among Organization for Economic Co-operation and Development (OECD) countries for over ten years [5,6]. In 2020, the suicide rate among older adults was 41.7 per 100,000 people in South Korea [7]. Under these circumstances, suicide among older adults in South Korea requires serious attention, especially considering that the country’s aging rate is the fastest in the world [5].
Suicide is directly related to suicide attempts, which occur in the reciprocal process of various risk factors, including socioeconomic, biological, and psychological factors [8]; those who have contemplated suicide are at higher risk for suicide attempts compared to those who have not [9]. Suicidal ideation is the most salient short-term warning sign preceding suicidal attempts [10,11]. Furthermore, older adults commit suicide without expressing their suicidal intent following long-term experiences of suicidal ideation, and the success rate of these suicidal attempts is high [11,12]. Jeon [13] found that 98.5% of older adults who had attempted suicide had also experienced suicidal ideation, indicating a more deliberate tendency than other age groups. Thus, the optimal strategy for reducing suicide attempts should identify risk factors for suicidal ideation and intervene based on these factors [14,15].
Previous studies [16,17,18] with older adults have reported that their suicidal ideation is related to physical factors (e.g., various physical changes and disease morbidities due to aging) and social factors (e.g., social isolation and lack of support), economic hardship, or psychological factors (e.g., depression). According to a recent study, reasons why older adults consider suicide include diseases and disabilities (37.5%), economic hardship (28.1%), loneliness and social isolation (15.9%), and family conflicts (11.0%) [19]. Additionally, older adults occasionally suffer from comorbidities of various diseases, such as stroke, heart disease, and chronic lung disease, and depression is highly likely to accompany the deterioration of individuals’ physical health [20,21]. Furthermore, depression is the most common mental health issue connected to suicidal ideation [11,21,22]. A survey [23] revealed that 21.1% of older adults in South Korea were experiencing depression, 6.7% had thoughts about suicide, and 13.2% had attempted suicide. Moreover, the absence of a spouse, living alone, being male, and loneliness are predictors of suicidal ideation among older adults [24,25,26]. Because suicidal ideation among older adults is related to various complex factors [12], research should identify these to prepare a person-centered approach strategy.
The life expectancy of Koreans is 83.3 years, and old age is prolonging along with the increase in older adult population. Age is one of the most important variables to consider in understanding the life of a prolonged old age [27]. Recognizing older adults over 65 years as a homogeneous group ignores the differences that exist within the older adult group [27], and it is also important to consider various characteristics by subdividing old age to prepare policies for these older adults. In general, old age is divided into older adults in youngest-old adults (ages 65 to 74 years) and old-old adults (75 years or older). In Korea, youngest-old adults make up 8.9% of the total population, which is higher than old-old adults (6.7%) [28]. Previous studies have reported that the lives and experiences of youngest-old adults and old-old adults are different [29,30], and the characteristics related to suicide and suicide ideation differ between youngest-old adults and old-old adults; thus, an approach tailored to age group is required [29,31]. Notably, mental health may deteriorate for youngest-old adults and lead to suicidal ideation. Individuals begin to experience a lack of economic support and role loss due to weakened social support, such as retirement, infrequent social activity, and declining physical functioning [29,30,31,32]. Thus, this study aims to identify factors related to suicidal ideation among youngest-old adults, utilizing data from the National Health and Nutrition Examination Survey (a large-scale national survey in South Korea) and using a decision tree analysis to predict the specific combinations of characteristics among youngest-old adults at high risk for suicide. The specific objectives of this study are described below.
  • To identify factors related to suicidal ideation in young older adults in South Korea.
  • To predict the specific complex characteristics of individuals at high risk to predict suicidal ideation in the young older adults in South Korea.

2. Materials and Methods

This study is a secondary analysis of data from Year 1 (2019) of Korea’s Eighth National Health and Nutrition Examination Survey. This survey was approved by the Institutional Review Board (2018-01-03-C-A) of the Korea Disease Control and Prevention Agency (KCDA), and the de-identified data can be downloaded from the agency’s website [33].

2.1. Sample and Background

The Korean National Health and Nutrition Examination Survey [33] collects various health-related information, including health level and behavior, nutrition and food intake, and prevalence of chronic diseases. Furthermore, the data have been used in many studies on health promotion, disease prevention, and developing health policy and programs [16,34,35,36]. The survey’s target population is individuals over the age of one residing in South Korea, and it employs two-stage stratified cluster sampling. A total of 8110 participated in the National Health and Nutrition Examination Survey in 2019. Among those included, there were 1018 youngest-older adults, and we removed missing data from the suicidal ideation variable (n = 48). Then, this study analyzed a sample of 970 South Korean youngest-old adults (65 to 74 years) [37].

2.2. Measurements

2.2.1. Socioeconomic Characteristics

The socioeconomic characteristics assessed in the survey included gender, education level, residential location, employment status, personal income level, family living situation, and spousal status. Gender was divided into male and female, education level was divided into high school graduate or lower and college graduate or higher, and the residential location was divided into “dong” (as urban, lived in a city) and “eup/myeon” (as rural, lived in a town or township). For employment status, “Yes” and “No” were assigned to the employed and the unemployed or economically inactive populations, respectively, and individual income level was divided into quartiles (high, middle-high, middle-low, and low) [33]. For family living situations, “Yes” and “No” indicated respondents living with their family and those who were not, respectively. Furthermore, “Yes” and “No” were used to indicate respondents with a spouse and those without one.

2.2.2. Health-Related Characteristics

Items assessing health-related characteristics included smoking, drinking, sleep, health examination, obesity, hypertension, diabetes, arthritis, physical activity, restricted activity, depression, stress, perceived health, and health-related quality of life. For smoking and drinking, “Yes” and “No” were used to indicate experience or lack thereof, and sleep time duration was divided into categories of 7–8 h (recommend), 5–6 h or 9 h or less (appropriate), and less than 5 h or more than 9 h (inappropriate) [38]. For the health examination, “Yes” and “No” indicated those who had a health checkup in the past two years and those who had not, respectively. For obesity, those with a body mass index of 25 kg/m2 or more were considered “obese”, while those with a body mass index less than 25 kg/m2 were considered “non-obese”. Hypertension was evaluated according to three stages: normal (not corresponding to hypertension or pre-hypertension stages with systolic blood pressure (SBP) < 120 mmHg and diastolic blood pressure (DBP) < 80 mmHg), pre-hypertension (not corresponding to a hypertension stage with 120 mmHg ≤ SBP < 140 mmHg and 80 mmHg ≤ DBP < 90 mmHg), and hypertension (SBP ≥ 140 mmHg or DBP ≥ 90 mmHg or cases in which the respondent had taken any antihypertensive drugs). Diabetes was evaluated according to three stages: normal (not corresponding to diabetes and pre-diabetes stages with a fasting blood sugar level less than 100 mg/dL or a glycated hemoglobin level less than 5.7%), pre-diabetes (not corresponding to diabetes with a fasting blood sugar level of 100–125 mg/dL or a glycated hemoglobin level was 5.7% and 6.4%), and diabetes (a fasting blood sugar level of 126 mg/dL or more, a medical diagnosis, usage of a hypoglycemic agent or insulin injection, or a glycated hemoglobin level of 6.5% or more). For arthritis, “Yes” and “No” were assigned to cases in which a doctor had diagnosed arthritis (osteoarthritis or rheumatoid arthritis) and those in which there was not such a diagnosis, respectively.
For physical activity, “Yes” and “No” were assigned to cases in which respondents had engaged in physical activities for a considerable period each week (2.5 h or more of moderate-intensity physical activity, 1.25 h or more of high-intensity physical activity, or both activities combined) and those in which they had not, respectively. For restricted activity, “Yes” and “No” were assigned to cases in which respondents were currently restricted in their daily lives and social activities due to health problems or physical/mental disabilities and those who were not, respectively. For depression, “Yes” and “No” were assigned to cases in which respondents felt sadness or hopelessness to the extent that it interfered with their daily lives for two or more consecutive weeks over the last year, and those who did not, respectively. Stress was divided into “high” and “low”, depending on the stress level experienced in daily life. Perceived health was operationalized as the subjective evaluation of one’s health on a 5-point scale (1 = Strongly Agree, 5 = Strongly Disagree). This study reversed the scale such that higher scores indicated better-perceived health. The EuroQOL-5D index evaluated health-related quality of life [33], wherein higher weighted scores correspond to a higher quality [39].

2.2.3. Suicidal Ideation

For suicidal ideation, “Yes” and “No” were assigned to cases in which respondents answered “I have” and “I have not”, respectively, to the question “Have you ever seriously considered suicide in the past 12 months?”.

2.3. Data Analysis

We conducted the analyses through complex samples analysis by considering weight, stratification, and cluster variables because the Korean National Health and Nutrition Examination Survey was designed with a complex sample. All analyses were performed in SPSS 27.0, setting the significance level at 95%. We calculated frequencies, percentages, means, and standard errors to describe respondents’ socioeconomic and health-related characteristics. The complex samples’ crosstabs test and a general linear model analyzed each factor’s significance for suicidal ideation. Then, logistic regression analysis identified significant socioeconomic and health-related factors related to suicidal ideation (Aim 1). A decision tree analysis predicted the specific complex characteristics of the group at high risk for suicidal ideation (Aim 2). The algorithm was classification and regression tree (CRT); the respective growth limits of the parent node and child node were set to 2% and 1%, and the maximum tree depth was set to 5. Ten-fold cross-validation confirmed the model’s stability, and the risk estimate value was 0.069.

3. Results

3.1. The Characteristics and Suicidal Ideation among the Subjects

Of the 970 samples that we analyzed, 7.3% (69 participants) responded that they had seriously considered suicide in the past 12 months. The proportion of the subjects in each characteristic is included in Table 1 and Table 2.

3.2. Relationship between Socioeconomic Characteristics and Suicidal Ideation

Table 1 shows the relationship between respondents’ socioeconomic characteristics and suicidal ideation. Among socioeconomic characteristics suicidal ideation was significantly related to education level (χ2 = 4.75, p = 0.031) and personal income level (χ2 = 7.28, p < 0.001). Suicidal ideation was significantly more common among those with an education level less than or equal to high school graduation and those whose personal income level was “low”.

3.3. Relationship between Health-Related Characteristics and Suicidal Ideation

Table 2 displays the relationship between respondents’ health-related characteristics and suicidal ideation. Among health-related characteristics, suicidal ideation was significantly related to restricted activity (χ2 = 9.26, p = 0.003), depression (χ2 = 92.19, p < 0.001), perceived stress (χ2 = 43.47, p < 0.001), perceived health (t = 5.18, p < 0.001), and health-related quality of life (t = 3.73, p < 0.001). Suicidal ideation was significantly more common when respondents had experienced activity restriction, depression, and high-level stress. The scores for perceived health and health-related quality of life were lower in the group with a history of suicidal ideation.

3.4. Factors Related to Suicidal Ideation

Table 3 presents factors related to suicidal ideation. The regression analysis included the variables significantly correlated between socioeconomic, health-related factors and suicidal ideation in Table 1 and Table 2. Suicidal ideation was related to personal income level, depression, stress, and perceived health. Suicidal ideation became more common as personal income level decreased (OR = 1.48, 95% CI = 1.04–2.12), when respondents had experienced depression that interfered with daily life for two consecutive weeks (OR = 9.28, 95% CI = 4.57–18.84), as perceived stress levels increased (OR = 2.42, 95% CI = 1.11–5.28), and when respondents reported relatively low perceived health (OR = 1.88, 95% CI = 1.23–3.11).

3.5. Predicting the Complex Characteristics of Those at High Risk for Suicidal Ideation

The decision tree analysis predicted the characteristics of the group at high risk for suicidal ideation based on the factors derived from the regression analysis. Suicidal ideation was predicted by combining depression, personal income level, and perceived health (p < 0.05); thus, suicidal ideation may occur via the interaction of these three characteristics (64.6%, Node 7; Figure 1). The high-risk group possessed all of the following characteristics: depression, low personal income level (middle-high or less), and low perceived health (1.5 points or less).

4. Discussion

Responding to the urgent need worldwide to devise suicide prevention measures tailored to older adults, this study uncovered specific complex characteristics of those at high risk for suicidal ideation. The results provide specific information on this high-risk group of youngest-old adults, which should be prioritized when creating suicide prevention strategies.
First, this study showed through regression analysis that depression, stress, personal income level, and perceived health are significantly related to suicidal ideation in youngest-old adults. Notably, the high correlation between depression and suicidal ideation is consistent with previous studies [10,16,21,35,40,41,42,43]. Paik [29] identified that depression was higher in youngest-old adults with loss of health, economy, and role. Lee et al. [44] reported that 91.7% of older adults with suicidal ideation had been diagnosed with depression. Hu et al. [22] found that depression mediates other variables’ relationships to suicidal ideation among older adults. As the opportunity to participate in social activities decreases due to retirement, youngest-old adults tend to experience loss and depression, resulting in an increased incidence of suicidal ideation [45]. However, not all older adults who have suicidal ideation attempt suicide. Thus, social participation, social support, and social cohesion, which effectively mitigate depression, should be encouraged [45]. Notably, social support can reduce suicidal ideation and depression or stress [45,46].
In the same context, the relatively high rate of suicidal ideation among older adults exposed to high-level stress can be explained based on previous findings that stress is highly correlated with depression [33,47]. Perceived stress is an important factor that increases identification of individuals with higher risk of suicidal ideation among older adults with depression [48]. This result may be attributed to tensions and pressures about an unforeseeable future as individuals experience aging [49], highlighting the need to consider depression and stress management in devising suicide prevention strategies.
Low personal income levels can lead to stress and depression, poverty, loss of social roles, and weakened physical health, increasing rates of suicidal ideation [22,31,32,45,50]. Youngest-old adults may experience suicidal ideation due to various life changes after retirement, including suddenly weakened social support and decreased income [51]. Supporting this reasoning, a recent survey of older adults in South Korea revealed that the main reason for suicidal ideation was economic hardship; 27.7% of these older adults mentioned the issue of living expenses [52], and their annual gross income was proportional to their education level [45,53]. The regression analysis in this study did not show economic hardship as a significant factor, which is consistent with the results of the univariate analysis that demonstrated that suicidal ideation was more common among those with less education (high school graduates or lower). Additionally, many recent surveys have confirmed that economic hardship is a significant predictor of suicidal ideation among older adults [16,32,45], which has important implications for identifying subgroups of youngest-old adults at high risk for suicide [50].
This study revealed that suicidal ideation was more common among those with low perceived health. Older adults occasionally experience difficulties in daily life, leading to loss of usual roles and social contact [54]. These results are consistent with those of a previous study [55] that reported that older adults who perceived their physical health as “bad”, including having activities of daily living (ADL) disorders, showed significantly higher rates of suicidal ideation compared to those who did not [34,56]. Restrictions on social life among older adults in the local community induce social isolation and loneliness and affect depression, increasing suicidal ideation [26]. Thus, management strategies organizing timely visits and establishing a support network using local community resources are crucial for older adults living alone or socially inactive [22,57].
In this study, to prepare a person-centered prevention strategy for suicidal ideation, we identified a high-risk group by combining related factors on the suicidal ideation derived in regression analysis. The decision tree analysis determined that combining the following three characteristics predicted a higher risk for suicidal ideation among youngest-old adults: depression, low income (moderate-high or less), and low perceived health (cutoff point = 1.5 points). Additionally, there is an interaction among physical, psychological, and socioeconomic factors [32,58]. Therefore, it necessary to classify youngest-old adults exhibiting all three characteristics into a high-risk group that should be prioritized when formulating suicide prevention strategies. Suicidal ideation is a strong predictor of suicide attempts [22], and this association is an essential consideration in suicide prevention. Thus, this study provides important insights for identifying high-risk groups among youngest-old adults and has implications for establishing targeted suicide prevention strategies. The findings could help lower the suicide rate among older adults in South Korea and enhance healthcare workers’ ability to discover and manage related issues.
This study has several limitations. First, the data originated from a self-report questionnaire, creating the possibility of subjective bias in responses. Second, since this study is cross-sectional, it cannot interpret the factors related to suicidal thoughts as causal relationships. Therefore, future studies could consider using longitudinal analysis to causally identify and interpret the influence factors. Third, suicidal ideation among youngest-old adults may not necessarily lead to suicide attempts. Fourth, the secondary data utilized in this study may have limitations in identifying all factors related to suicidal ideation among youngest-old adults, especially a history of physical and mental illness, which was not objectively measured. Fifth, this study’s results differed from previous studies [16,59] exploring factors influencing suicidal ideation in older adults age 65 years or older based on the same survey data; thus, future research should consider a variety of respondents, such as other respondent age groups.

5. Conclusions

This study identified the specific complex characteristics of youngest-old adults at high risk for suicidal ideation in South Korea, with the world’s highest suicide rate and a rapidly aging population. This high-risk group exhibited depression, low personal income, and low perceived health. The results suggest relevant criteria for selecting target demographics in establishing suicide prevention strategies for older adults.
Furthermore, this study has two important implications. First, target selection and customized interventions should be implemented based on vulnerable individuals’ characteristics to prevent suicide among older adults in South Korea. Second, although this study revealed that physical, psychological, and socioeconomic factors are jointly related to suicidal ideation among youngest-old adults, future research should expand the model to include other potentially influential factors.

Author Contributions

Conceptualization, E.K. and J.-S.Y.; data curation, J.-S.Y.; formal analysis, J.-S.Y.; methodology, J.-S.Y.; writing—original draft, E.K. and J.-S.Y.; writing—review and editing, E.K. and J.-S.Y. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable; this study is a secondary analysis using open dataset.

Informed Consent Statement

Not applicable to this secondary study. This analysis used de-identified data on the Korea Disease Control and Prevention Agency (KCDA) website.

Data Availability Statement

Researchers who want to use microdata and analytic guidelines can be downloaded from the KCDA website (https://knhanes.kdca.go.kr/knhanes/main.do (accessed on 16 April 2021)) in Korean.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Foroughan, M.; Rostami, M.; Jalal Younesi, S. Determinants of suicidal ideation among older adults: A cross-sectional survey in Iran. GeroPsych 2021, 34, 91–99. [Google Scholar] [CrossRef]
  2. Satorres, E.; Ros, L.; Meléndez, J.; Serrano, J.; Latorre, J.; Sales, A. Measuring elderly people’s quality of life through the Beck Hopelessness Scale: A study with a Spanish sample. Aging Ment. Health 2018, 22, 239–244. [Google Scholar] [CrossRef]
  3. Conejero, I.; Olié, E.; Courtet, P.; Calati, R. Suicide in older adults: Current perspectives. Clin. Interv. Aging 2018, 13, 691–699. [Google Scholar] [CrossRef] [PubMed]
  4. Paraschakis, A.; Douzenis, A.; Michopoulos, I.; Christodoulou, C.; Vassilopoulou, K.; Koutsaftis, F.; Lykouras, L. Late onset suicide: Distinction between “young-old” vs.“old-old” suicide victims. How different populations are they? Arch. Gerontol. Geriatr. 2012, 54, 136–139. [Google Scholar] [CrossRef] [PubMed]
  5. Projected Population by Age Group (Korea). Available online: https://www.index.go.kr/potal/stts/idxMain/selectPoSttsIdxSearch.do?idx_cd=1024&stts_cd=102401&freq=Y (accessed on 18 April 2022).
  6. Raschke, N.; Mohsenpour, A.; Aschentrup, L.; Fischer, F.; Wrona, K.J. Socioeconomic factors associated with suicidal behaviors in South Korea: Systematic review on the current state of evidence. BMC Public Health 2022, 22, 129. [Google Scholar] [CrossRef]
  7. Suicidal Rate of Elders. Available online: https://kosis.kr/statHtml/statHtml.do?orgId=538&tblId=DT_538002_2020F007&vw_cd=MT_ZTITLE&list_id=V_3_202_001_006&seqNo=&lang_mode=ko&language=kor&obj_var_id=&itm_id=&conn_path=MT_ZTITLE (accessed on 2 March 2022).
  8. Wasserman, D. Suicide: An Unnecessary Death; Oxford University Press: Oxford, UK, 2016. [Google Scholar]
  9. Chin, Y.R.; Kim, C.; Park, I.; Han, S.Y. The relationship between the prevalence of suicidal ideation among older adults and individual/regional factors. J. Korean Acad. Community Health Nurs. 2020, 31, 577–590. [Google Scholar] [CrossRef]
  10. McHugh, C.M.; Corderoy, A.; Ryan, C.J.; Hickie, I.B.; Large, M.M. Association between suicidal ideation and suicide: Meta-analyses of odds ratios, sensitivity, specificity and positive predictive value. BJPsych Open 2019, 5, e18. [Google Scholar] [CrossRef]
  11. Yoo, B.S.; Jeong, K.H. A study on the determinants of elderly suicidal idea: Focused on the Gyeonngi province. Soc. Work Pract. Res. 2016, 13, 215–250. [Google Scholar]
  12. Suicide and Older Adults: What You Should Know. Available online: https://www.ncoa.org/article/suicide-and-older-adults-what-you-should-know (accessed on 10 July 2022).
  13. Jeon, H.J. Depression and suicide. J. Korean Med. Assoc. 2011, 54, 370–375. [Google Scholar] [CrossRef]
  14. Lee, S.-Y.; Atteraya, M.S. Depression, poverty, and abuse experience in suicide ideation among older Koreans. Int. J. Aging Hum. Dev. 2019, 88, 46–59. [Google Scholar] [CrossRef]
  15. Ryu, S.I.; Park, Y.-H. Factors related to suicide ideation in older women living alone. Korean J. Adult Nurs. 2020, 32, 78–87. [Google Scholar] [CrossRef]
  16. Shiraly, R.; Mahdaviazad, H.; Zohrabi, R.; Griffiths, M.D. Suicidal ideation and its related factors among older adults: A population-based study in Southwestern Iran. BMC Geriatrics 2022, 22, 371–380. [Google Scholar] [CrossRef] [PubMed]
  17. Van Orden, K.; Conwell, Y. Suicides in late life. Curr. Psychiatry Rep. 2011, 13, 234–241. [Google Scholar] [CrossRef]
  18. Conwell, Y.; Orden, K.V.; Caine, E.D. Suicide in older adults. Psychiatr. Clin. N. Am. 2011, 34, 451–468. [Google Scholar] [CrossRef] [PubMed]
  19. Social Survey in 2014. Available online: https://kosis.kr/search.do (accessed on 18 April 2022).
  20. Mitchell, P.B.; Harvey, S.B. Depression and the older medical patient—When and how to intervene. Maturitas 2014, 79, 153–159. [Google Scholar] [CrossRef]
  21. Song, Y.; Son, J.; Park, S. An analysis of eco-systematic factors influencing suicidal ideation of the elderly who are living alone. Hanguk Nonyonhak 2010, 30, 643–660. [Google Scholar]
  22. Hu, C.; Zhao, D.; Gong, F.; Zhao, Y.; Li, J.; Sun, Y. Risk factors for suicidal ideation among the older people living alone in rural region of China: A path analysis. Medicine 2020, 99, 321330. [Google Scholar] [CrossRef] [PubMed]
  23. Depression Symptom of Elders. Available online: https://kosis.kr/statHtml/statHtml.do?orgId=117&tblId=DT_117071_019&vw_cd=MT_ZTITLE&list_id=117_11771_003_117_11771_003_06&seqNo=&lang_mode=ko&language=kor&obj_var_id=&itm_id=&conn_path=MT_ZTITLE (accessed on 21 October 2021).
  24. Rana, A.Q.; Qureshi, A.R.M.; Mumtaz, A.; Abdullah, I.; Jesudasan, A.; Hafez, K.K.; Rana, M.A. Associations of pain and depression with marital status in patients diagnosed with Parkinson’s disease. Acta Neurol. Scand. 2016, 133, 276–280. [Google Scholar] [CrossRef] [PubMed]
  25. Ahn, D.-H.; Lee, Y.-J.; Jeong, J.-H.; Kim, Y.-R.; Park, J.-B. The effect of post-stroke depression on rehabilitation outcome and the impact of caregiver type as a factor of post-stroke depression. Ann. Rehabil. Med. 2015, 39, 74–80. [Google Scholar] [CrossRef]
  26. Holvast, F.; Burger, H.; de Waal, M.M.; van Marwijk, H.W.; Comijs, H.C.; Verhaak, P.F. Loneliness is associated with poor prognosis in late-life depression: Longitudinal analysis of the Netherlands study of depression in older persons. J. Affect. Disord. 2015, 185, 1–7. [Google Scholar] [CrossRef] [PubMed]
  27. Life Expectancy by Sex and Education Level: Health at a Glance. 2021. Available online: https://www.oecd-ilibrary.org/sites/ae3016b9-en/1/3/3/2/index.html?itemId=/content/publication/ae3016b9-en&_csp_=ca413da5d44587bc56446341952c275e&itemIGO=oecd&itemContentType=book (accessed on 1 June 2022).
  28. Population of Older Adults. Available online: https://www.akomnews.com/bbs/board.php?bo_table=news&wr_id=41543 (accessed on 1 June 2022).
  29. Paik, J.-E. A study on the loss experiences, aging anxiety, and depression of young-old and old-old. J. Digit. Converg. 2018, 16, 403–413. [Google Scholar] [CrossRef]
  30. Jeong, K.H.; Ko, A.R. A study on the influencing factors of suicidal ideation of the young-old and old-old elderly in South Korea: Focusing on the individual, family, and community system factors. Korean J. Fam. Soc. Work 2016, 53, 45–78. [Google Scholar] [CrossRef]
  31. Wu, Z.-Q.; Sun, L.; Sun, Y.-H.; Zhang, X.-J.; Tao, F.-b.; Cui, G.-H. Correlation between loneliness and social relationship among empty nest elderly in Anhui rural area, China. Aging Ment. Health 2010, 14, 108–112. [Google Scholar] [CrossRef] [PubMed]
  32. Handley, T.E.; Hiles, S.A.; Inder, K.J.; Kay-Lambkin, F.J.; Kelly, B.J.; Lewin, T.J.; McEvoy, M.; Peel, R.; Attia, J.R. Predictors of suicidal ideation in older people: A decision tree analysis. Am. J. Geriatr. Psychiatry 2014, 22, 1325–1335. [Google Scholar] [CrossRef] [PubMed]
  33. Korea National Health & Nutrition Examination Survey. Available online: https://knhanes.kdca.go.kr/knhanes/main.do (accessed on 12 January 2022).
  34. Kim, S.H. Suicidal ideation and suicide attempts in older adults: Influences of chronic illness, functional limitations, and pain. Geriatr. Nurs. 2016, 37, 9–12. [Google Scholar] [CrossRef] [PubMed]
  35. Koo, C.Y.; Kim, J.S.; Yu, J. A study on factors influencing elders’ suicidal ideation: Focused on comparison of gender differences. J. Korean Acad. Community Health Nurs. 2014, 25, 24–32. [Google Scholar] [CrossRef]
  36. Park, E.-O.; Lee, H.Y. Factors influencing suicidal ideation among korean adults by age: Results of the 2010–2011 korean health and nutrition examination survey. Community Ment. Health J. 2015, 51, 987–993. [Google Scholar] [CrossRef] [PubMed]
  37. Nam, S.; Kim, S.; Kim, H.J. Gender differences in the effect of mutual spousal support on depression in young-old age. Health Soc. Welf. Rev. 2018, 38, 257–289. [Google Scholar]
  38. Hirshkowitz, M.; Whiton, K.; Albert, S.M.; Alessi, C.; Bruni, O.; DonCarlos, L.; Hazen, N.; Herman, J.; Katz, E.S.; Kheirandish-Gozal, L.; et al. National Sleep Foundation’s sleep time duration recommendations: Methodology and results summary. Sleep Health 2015, 1, 40–43. [Google Scholar] [CrossRef] [PubMed]
  39. Jang, J.; Jung, H.-S.; Kim, S.; Lee, K.-U. Associations between suicidal ideation and health-related quality of life among community-dwelling stroke survivors: 2013-2017 Korea national health and nutrition examination survey. Qual. Life Res. 2021, 31, 403–412. [Google Scholar] [CrossRef]
  40. Kim, H.; Lee, A.; Lee, S.I.; Kim, Y.; Jung, H.-Y.; Kim, S.-G. Risk factors for suicidal ideation in the elderly. J. Korean Neuropsychiatr. Assoc. 2015, 54, 468–474. [Google Scholar] [CrossRef]
  41. Lee, H.S.; Lee, D. Structural equation modeling of suicidal ideation and associated factors among elderly women in Korea. Korean J. Health Promot. 2014, 14, 162–171. [Google Scholar] [CrossRef]
  42. Lee, S.J.; Lee, E.J. Factors associated with suicidal ideation of elderly people based on complete enumeration of a community setting. J. Korean Acad. Psychiatr. Ment. Health Nurs. 2019, 28, 393–403. [Google Scholar] [CrossRef]
  43. Kim, B.J.; Kihl, T. Suicidal ideation associated with depression and social support: A survey-based analysis of older adults in South Korea. BMC Psychiatry 2021, 21, 409. [Google Scholar] [CrossRef]
  44. Lee, S.-H.; Tsai, Y.-F.; Chen, C.-Y.; Huang, L.-B. Triggers of suicide ideation and protective factors of actually executing suicide among first onset cases in older psychiatric outpatients: A qualitative study. BMC Psychiatry 2014, 14, 269. [Google Scholar] [CrossRef]
  45. Psychosocial Anxiety and Mental Health in Old Age. Available online: https://www.kihasa.re.kr/publish/regular/hsw/view?seq=22744&volume=20382 (accessed on 1 June 2022).
  46. Endo, G.; Tachikawa, H.; Fukuoka, Y.; Aiba, M.; Nemoto, K.; Shiratori, Y.; Matsui, Y.; Doi, N.; Asada, T. How perceived social support relates to suicidal ideation: A Japanese social resident survey. Int. J. Soc. Psychiatry 2014, 60, 290–298. [Google Scholar] [CrossRef]
  47. Ku, J.-K.; Song, I.-J. A convergence study on the effects of stress on suicidal ideation in the elderly’s: Mediating effects of depression. J. Korea Converg. Soc. 2020, 11, 301–310. [Google Scholar] [CrossRef]
  48. Bickford, D.; Morin, R.; Nelson, J.C.; Mackin, R.S. Determinants of suicide-related ideation in late life depression: Associations with perceived stress. Clin. Gerontol. 2020, 43, 37–45. [Google Scholar] [CrossRef]
  49. Kessler, E.-M.; Tempel, J.; Wahl, H.-W. Concerns about one’s aging. GeroPsych 2014, 27, 81–86. [Google Scholar] [CrossRef]
  50. Hung, G.C.-L.; Kwok, C.-L.; Yip, P.S.; Gunnell, D.; Chen, Y.-Y. Predicting suicide in older adults–a community-based cohort study in Taipei City, Taiwan. J. Affect. Disord. 2015, 172, 165–170. [Google Scholar] [CrossRef]
  51. Income Inequalities, Social Support and Depressive Symptoms among Older Adults in Europe: A Multilevel Cross-Sectional Study. Available online: https://link.springer.com/content/pdf/10.1007/s10433-021-00670-2.pdf (accessed on 1 June 2022).
  52. Choi, M.; Kim, D.-H.; Lee, K.; Yi, J.-S. Physical, psychological, and social risk factors affecting suicidal ideation among the elderly. J. Korean Neuropsychiatr. Assoc. 2015, 54, 459–467. [Google Scholar] [CrossRef]
  53. Annual Income of Older Adults. Available online: https://kosis.kr/statHtml/statHtml.do?orgId=117&tblId=DT_117071_029&vw_cd=MT_ZTITLE&list_id=117_11771_003_05&seqNo=&lang_mode=ko&language=kor&obj_var_id=&itm_id=&conn_path=MT_ZTITLE (accessed on 18 April 2022).
  54. Erlangsen, A.; Stenager, E.; Conwell, Y. Physical diseases as predictors of suicide in older adults: A nationwide, register-based cohort study. Soc. Psychiatry Psychiatr. Epidemiol. 2015, 50, 1427–1439. [Google Scholar] [CrossRef] [PubMed]
  55. Kim, H.-K.; Ko, S.-H.; Chung, S.-H. Suicidal ideation and risk factors among the elderly in Korea. J. Korean Public Health Nurs. 2010, 24, 82–92. [Google Scholar] [CrossRef]
  56. Bang, S.Y. Loneliness Suicide in older adults: Current perspectives and suicidal ideation according to character type in elderly. J. Korea Contents Assoc. 2014, 14, 319–327. [Google Scholar] [CrossRef]
  57. Huang, L.B.; Tsai, Y.F.; Liu, C.Y.; Chen, Y.J. Influencing and protective factors of suicidal ideation among older adults. Int. J. Ment. Health Nurs. 2017, 26, 191–199. [Google Scholar] [CrossRef] [PubMed]
  58. Oude Voshaar, R.C.; Van Der Veen, D.C.; Kapur, N.; Hunt, I.; Williams, A.; Pachana, N.A. Suicide in patients suffering from late-life anxiety disorders; a comparison with younger patients. Int. Psychogeriatr. 2015, 27, 1197–1205. [Google Scholar] [CrossRef]
  59. Kim, K.; Kim, J.-S.; Lee, B.; Lee, E.; Ahn, Y.; Choi, M. A study about the factors affecting the suicidal thought in Korean elders. J. Korean Acad. Psychiatr. Ment. Health Nurs. 2010, 19, 391–399. [Google Scholar] [CrossRef]
Figure 1. The complex characteristics associated with a high risk for suicidal ideation.
Figure 1. The complex characteristics associated with a high risk for suicidal ideation.
Ijerph 19 10028 g001
Table 1. The socioeconomic characteristics associated with suicidal ideation among the subjects.
Table 1. The socioeconomic characteristics associated with suicidal ideation among the subjects.
Variables Total
(N = 970)
Suicidal Ideation
No
(n = 901)
Yes
(n = 69)
Rao–Scott χ2
n (%)n (%)n (%)
GenderMale427 (47.7)399 (93.3)28 (6.7)0.39 (0.535)
Female543 (52.3)502 (92.1)41 (7.9)
Education level≤High school817 (87.0)757 (92.7)60 (7.3)4.75 (0.031)
University106 (13.0)104 (98.3)2 (1.7)
Living locationeup/myeon723 (77.5)670 (92.4)53 (7.6)0.37 (0.544)
dong247 (22.5)231 (93.7)16 (6.3)
Economic activityYes388 (42.7)365 (94.9)23 (5.1)1.92 (0.168)
No538 (57.3)497 (92.0)41 (8.0)
Personal incomeHigh240 (26.7)235 (98.1)5 (1.9)7.28 (<0.001)
Middle-high235 (24.1)225 (95.7)10 (4.3)
Middle-low252 (24.5)228 (89.3)24 (10.7)
Low239 (24.6)209 (86.9)30 (13.1)
Family living situationYes792 (84.7)737 (92.9)55 (7.1)0.31 (0.581)
No178 (15.3)164 (91.6)14 (8.4)
Presence of spouseYes735 (78.1)683 (93.2)52 (6.8)1.66 (0.200)
No226 (21.9)209 (90.4)17 (9.6)
N: unweighted; %: weighted; Rao–Scott χ2: a correlation between socioeconomic characteristics and suicidal ideation.
Table 2. The health-related characteristics associated with suicidal ideation among the subjects.
Table 2. The health-related characteristics associated with suicidal ideation among the subjects.
Variables Total
(N = 970)
Suicidal Ideation
No
(n = 901)
Yes
(n = 69)
Rao–Scott χ2 or t (p)
n (%) or
M ± SE
n (%) or
M ± SE
n (%) or
M ± SE
SmokingYes396 (43.6)367 (91.5)29 (8.5)0.93 (0.337)
No574 (56.4)534 (93.6)40 (6.4)
DrinkingYes787 (83.2)729 (92.2)58 (7.8)1.77 (0.186)
No183 (16.8)172 (95.1)11 (4.9)
Sleep time
(Weekday, hours)
7–8428 (44.3)402 (93.6)26 (6.4)1.33 (0.267)
5–6, 9439 (45.3)411 (92.8)28 (7.2)
<5 or >9103 (10.4)88 (88.4)15 (11.6)
Sleep time
(Weekend, hours)
7–8449 (46.2)425 (94.3)24 (5.7)1.70 (0.184)
5–6, 9412 (42.1)382 (91.9)30 (8.1)
<5 or >9109 (11.8)94 (89.1)15 (10.9)
Health examinationYes720 (77.8)673 (93.7)47 (6.3)1.01 (0.316)
No205 (22.2)188 (91.5)17 (8.5)
ObesityObese342 (35.1)316 (92.4)26 (7.6)0.04 (0.845)
Non-obese625 (64.9)582 (92.8)43 (7.2)
Blood pressureNormal155 (17.0)140 (91.2)15 (8.8)0.43 (0.649)
Pre-hypertension217 (22.2)207 (94.1)10 (5.9)
Hypertension597 (60.8)553 (92.5)44 (7.5)
GlucoseNormal188 (20.9)176 (94.9)12 (5.1)1.09 (0.335)
Pre-diabetes443 (51.2)415 (94.3)28 (5.7)
Diabetes264 (28.0)244 (91.3)20 (8.7)
ArthritisYes277 (28.7)256 (93.6)21 (6.4)0.09 (0.771)
No649 (71.3)606 (93.0)43 (7.0)
Physical activityYes348 (38.1)329 (94.5)19 (5.5)0.90 (0.345)
No576 (61.9)531 (92.4)45 (7.6)
Restricted activityYes124 (11.6)107 (86.6)17 (13.4)9.26 (0.003)
No802 (88.4)755 (94.1)47 (5.9)
DepressionYes129 (11.8)84 (63.3)45 (36.7)92.19 (<0.001)
No841 (88.2)817 (96.6)24 (3.4)
Perceived StressHigh164 (16.1)127(77.2)37 (22.8)43.47 (<0.001)
Low806 (83.9)774 (95.6)32 (4.4)
Perceived health 3.00 ± 0.033.05 ± 0.032.28 ± 0.135.18 (<0.001)
HRQoL 0.92 ± 0.010.92 ± 0.010.83 ± 0.033.73 (<0.001)
HRQoL = health-related of life; M = Mean; S = Standard error; N: unweighted; %: weighted; Rao–Scott χ2: a correlation between socioeconomic characteristics and suicidal ideation.
Table 3. Factors related to the suicidal ideation (N = 970).
Table 3. Factors related to the suicidal ideation (N = 970).
Variables Suicidal Ideation
OR95% CIp
Education level≤High school1.970.33–11.640.451
University1
Personal income (Ref: High)1.481.04–2.120.030
Restricted activityYes0.780.37–1.620.499
No1
DepressionYes9.284.57–18.84<0.001
No1
Perceived stressHigh2.421.11–5.280.026
Low1
Perceived health (Ref: Very good)1.881.23–3.110.016
HRQoL 0.990.79–1.240.927
HRQoL = health-related of life; Ref = reference value; OR = odds ratio; CI = confidence interval.
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

Kim, E.; Yi, J.-S. Factors Related to Suicidal Ideation and Prediction of High-Risk Groups among Youngest-Old Adults in South Korea. Int. J. Environ. Res. Public Health 2022, 19, 10028. https://doi.org/10.3390/ijerph191610028

AMA Style

Kim E, Yi J-S. Factors Related to Suicidal Ideation and Prediction of High-Risk Groups among Youngest-Old Adults in South Korea. International Journal of Environmental Research and Public Health. 2022; 19(16):10028. https://doi.org/10.3390/ijerph191610028

Chicago/Turabian Style

Kim, Eungyung, and Jee-Seon Yi. 2022. "Factors Related to Suicidal Ideation and Prediction of High-Risk Groups among Youngest-Old Adults in South Korea" International Journal of Environmental Research and Public Health 19, no. 16: 10028. https://doi.org/10.3390/ijerph191610028

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop