Associations between suicidal ideation and health-related quality of life among community-dwelling stroke survivors: 2013-2017 Korea National Health and Nutrition Examination Survey

Trajectories of self-rated health among community-dwelling individuals with depressive symptoms: A latent class growth analysis

BACKGROUND

This study identified differences between individuals with and without depression regarding demographic and socioeconomic variables, health behavior, health status, health care utilization, and self-rated health (SRH) to identify the depressed group's SRH trajectories.

METHODS

Data of individuals with (n = 589) and without (n = 6856) depression aged ≥20 from the 2013-2017 Korean Health Panel were analyzed. A chi-square test and t-tests examined differences in demographic and socioeconomic variables, health behaviors, health status, health care utilization, and the mean of SRH. Latent Growth Curve and Latent Class Growth Modeling identified SRH development trajectories and the most suitable latent classes explaining the trajectories, respectively. Multinomial logistic regression determined the predicting factors that classified latent classes.

RESULTS

The depressed group had a lower mean SRH than the non-depressed group among most variables. Three latent classes were identified, each showing different SRH trajectories. Body-mass index and pain/discomfort were predicting factors for the "poor" classes compared with the "moderate-stable" class; older age, less national health insurance, less physical activity, more pain/discomfort, and more hospitalization were predictors for the "poor-stable" class. The depressed group's mean SRH was "poor."

LIMITATIONS

Latent Class Growth Modeling in individuals with depression was based on experimental data; however, it needed to review other sample data to identify similar types of latent classes to those suggested in the current study.

CONCLUSIONS

Predictors of the "poor-stable" class that were identified in this study can contribute to the formulation of intervention plans for the health and welfare of individuals with depression.

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

(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.

Comparative Analysis of Stroke Patients with and without Sequelae: A Cross-Sectional Analysis Using the KOREA National Health and Nutrition Examination Survey (2016-2019)

(1) Background: We aimed to evaluate the association between sociodemographic factors and mental health problems and the sequelae of stroke in South Korea by analyzing the annual Korea National Health and Nutrition Examination Surveys (KNHANES) conducted from 2016 to 2019. (2) Methods: Data were obtained from 32,379 participants who participated in the KNHANES (2016-2019). A total of 567 participants diagnosed with stroke were included in this study. Patients were divided into two groups based on the presence of sequelae: (a) stroke patients with sequelae (n = 227, 40.0%) and (b) stroke patients without sequelae (n = 340, 60.0%). (3) Results: Compared to stroke patients without sequelae, those with sequelae were significantly associated with sex (male, 61.2% vs. 47.6%, p = 0.002), household income (lower half, 78.9% vs. 67.4%, p = 0.005), owning a house (60.4% vs. 68.5%, p = 0.048), marital status (unmarried, 7.05% vs. 1.76%, p < 0.001), depression (13.2% vs. 7.35%, p = 0.045), suicidal ideation (6.17% vs. 3.24%, p = 0.010), and suicide attempts (2.64% vs. 0.88%, p = 0.012). (4) Conclusions: Our study showed that poor sociodemographic factors and mental health problems were significantly associated with sequelae from stroke. Clinical physicians should therefore carefully screen for depression and suicidality in stroke patients with sequelae, especially in those with poor sociodemographic factors.