Age and sex‐related differences in risk factors for elderly suicide: Differentiating between suicide ideation and attempts

Lee, Hyuk; Seol, Ki Ho; Kim, Jun Won

doi:10.1002/gps.4794

Cited by 27 publications

(24 citation statements)

References 37 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Studies included in this article showed different lifestyle behaviors in different lifestages. In adolescent and young adults there are multiple important risk factors for suicide including psychosis, depression, low sleep satisfaction, high stress, substance abuse, alcohol consumption, smoking, sexual activity, internet addiction, interpersonal factors, personality disorders, anxiety or conduct disorders, eating disorders, and aggressive, irritable and antisocial tendencies ( 38 , 39 ). Though it has been demonstrated that school-based suicide prevention programs increase knowledge on suicide without really preventing suicidal behaviors ( 133 ), it seems necessary to consider prevention programs that identify substance abuse, educational competencies (literacy, study skills, time management), educational environment, school programs, social interactions, academic attainment, cognitive progress, emotional control, behavioral expectations, physical and moral development, and encouragement of active engagement in sports.…”

Section: Discussionmentioning

confidence: 99%

“…Im et al ( 38 ) examined 370,568 students with the aim of recognizing risk factors for suicidal ideation in adolescents found that low sleep satisfaction, high stress, alcohol consumption, smoking, and sexual activity, were significant lifestyle factors associated with suicidal ideation. Lee et al ( 39 ) in a sample of 860 adolescents confirmed the relationship between several lifestyle behaviors and suicide risk including sleep disturbance, internet game addiction, and interpersonal factors (e.g., family conflicts and peer problems). A recent systematic review of 17 studies recognized that, in adolescents, a diagnosis of binge eating disorder was predictive of suicidality, while a high body mass index (BMI) was not ( 40 ).…”

Section: Lifestyle Behavior and Suicide In Adolescents And Young Peopmentioning

confidence: 91%

“…Physical illness, chronic severe pain, debilitating disease, and diagnosis of a terminal illness are common antecedents to suicide in older adults ( 104 ). Lee et al ( 39 ) after analyzing age and sex-related features and suicide risk in the elderly stressed that the only stable risk factor for suicide in this age group was the negative perception of one's own health status.…”

Section: Lifestyle Behavior and Suicide In Older Adultsmentioning

confidence: 99%

See 2 more Smart Citations

Lifestyle Interventions and Prevention of Suicide

et al. 2018

View full text Add to dashboard Cite

Over the past years, there has been a growing interest in the association between lifestyle psychosocial interventions, severe mental illness, and suicide risk. Patients with severe mental disorders have higher mortality rates, poor health states, and higher suicide risk compared to the general population. Lifestyle behaviors are amenable to change through the adoption of specific psychosocial interventions, and several approaches have been promoted. The current article provides a comprehensive review of the literature on lifestyle interventions, mental health, and suicide risk in the general population and in patients with psychiatric disorders. For this purpose, we investigated lifestyle behaviors and lifestyle interventions in three different age groups: adolescents, young adults, and the elderly. Several lifestyle behaviors including cigarette smoking, alcohol use, and sedentary lifestyle are associated with suicide risk in all age groups. In adolescents, growing attention has emerged on the association between suicide risk and internet addiction, cyberbullying and scholastic and family difficulties. In adults, psychiatric symptoms, substance and alcohol abuse, weight, and occupational difficulties seems to have a significant role in suicide risk. Finally, in the elderly, the presence of an organic disease and poor social support are associated with an increased risk of suicide attempt. Several factors may explain the association between lifestyle behaviors and suicide. First, many studies have reported that some lifestyle behaviors and its consequences (sedentary lifestyle, cigarette smoking underweight, obesity) are associated with cardiometabolic risk factors and with poor mental health. Second, several lifestyle behaviors may encourage social isolation, limiting the development of social networks, and remove individuals from social interactions; increasing their risk of mental health problems and suicide.

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Lifestyle Behavior and Suicide In Adolescents And Young Peopmentioning

confidence: 91%

Section: Lifestyle Behavior and Suicide In Older Adultsmentioning

confidence: 99%

See 1 more Smart Citation

Lifestyle Interventions and Prevention of Suicide

et al. 2018

View full text Add to dashboard Cite

show abstract

“…[30][31][32] In terms of the mediating factors between these demographic or physical health-related variables, stress cognition, and depressive mood have been identified as some of the most influential factors in SI. Previous researches have reported that various demographic risk factors increase suicidality, including older age, 33 being an unmarried male, 34 and having lower economic status. 35 In a meta-analysis, alcohol abuse was also reported as a significant risk factor for SI [odds ratio (OR)= 1.86] as well as for suicide attempts and completed suicide.…”

Section: Depressive Mood: a Risk Factor And Possible Mediator Betweenmentioning

confidence: 99%

Prediction of Suicidal Ideation among Korean Adults Using Machine Learning: A Cross-Sectional Study

Yun

Yeo

et al. 2020

Psychiatry Investig

View full text Add to dashboard Cite

Objective Suicidal ideation (SI) precedes actual suicidal event. Thus, it is important for the prevention of suicide to screen the individuals with SI. This study aimed to identify the factors associated with SI and to build prediction models in Korean adults using machine learning methods.Methods The 2010–2013 dataset of the Korea National Health and Nutritional Examination Survey was used as the training dataset (n=16,437), and the subset collected in 2015 was used as the testing dataset (n=3,788). Various machine learning algorithms were applied and compared to the conventional logistic regression (LR)-based model.Results Common risk factors for SI included stress awareness, experience of continuous depressive mood, EQ-5D score, depressive disorder, household income, educational status, alcohol abuse, and unmet medical service needs. The prediction performances of the machine learning models, as measured by the area under receiver-operating curve, ranged from 0.794 to 0.877, some of which were better than that of the conventional LR model (0.867). The Bayesian network, LogitBoost with LR, and ANN models outperformed the conventional LR model.Conclusion A machine learning-based approach could provide better SI prediction performance compared to a conventional LR-based model. These may help primary care physicians to identify patients at risk of SI and will facilitate the early prevention of suicide.

show abstract

“…Although many suicide risk factors have been identified, it is difficult to predict the real reason for the high suicide rate in older adults . Previous studies have reported that ill health, loss of function due to aging, terminal illness, chronic pain, mental health problems—such as depression, social isolation, a lack of support systems—and financial difficulties were risk factors for death by suicide in older adults .…”

Section: Introductionmentioning

confidence: 99%

Poverty and suicide risk in older adults: A retrospective longitudinal cohort study

Choi

Kim

Shin

et al. 2019

Int J Geriat Psychiatry

View full text Add to dashboard Cite

Objectives The present study evaluated suicide risk within 1 year after discharge among older adults with stroke as a function of depression onset. Method We used the Korean National Health Insurance Service‐Senior cohort data and included first discharged patients with a stroke as the principal diagnosis. The comparison group was selected by a 1:2 case‐control propensity score matching for age, sex, Charlson comorbidity index, and diagnosis year between 2005 and 2012. Suicide deaths were measured by code for causes of death from Statistics Korea, and the main outcome was suicide death within 1 year following discharge. An adjusted hazard ratio (AHR) of suicidal risk was measured using a Cox proportional hazard model. Results In the total sample of 128 286 older adults (aged 63‐114 years), the higher suicidal risk was examined for stroke patients vs the comparison group (AHR = 1.4; 95% confidence interval [CI], 1.1‐1.8). Stroke patients with depression had an increased suicide risk (AHR = 2.9; 95% CI, 1.8‐4.8) but only for poststroke depression (AHR = 4.1; 95% CI, 1.8‐9.5). Pre and poststroke depression suicidality (AHR = 4.8; 95% CI, 2.1‐11.1) was also higher when compared to stroke patients without depression. Conclusions Poststroke patients are at increased suicidal risk during 1 year following discharge. Furthermore, patients who were diagnosed with depression after a stroke are more likely to commit suicide than stroke patients without depression. This suggests a necessity for early suicide preventive intervention for stroke patients while considering depressive symptomology.

show abstract

Age and sex‐related differences in risk factors for elderly suicide: Differentiating between suicide ideation and attempts

Cited by 27 publications

References 37 publications

Lifestyle Interventions and Prevention of Suicide

Lifestyle Interventions and Prevention of Suicide

Prediction of Suicidal Ideation among Korean Adults Using Machine Learning: A Cross-Sectional Study

Poverty and suicide risk in older adults: A retrospective longitudinal cohort study

Contact Info

Product

Resources

About