Comparative Analysis of Stroke Patients with and without Sequelae: A Cross-Sectional Analysis Using the KOREA National Health and Nutrition Examination Survey (2016–2019)
by
,
Chi Woong Oh
1, 
Sang Hyuk Lee
1,
Taek Min Nam
1,
Ji Hwan Jang
1,
Young Zoon Kim
1
,
Kyu Hong Kim
1,
Do-Hyung Kim
2,
Nak Gyeong Ko
3 and
Seung Hwan Kim
1,* 1
Department of Neurosurgery, Samsung Changwon Hospital, Sungkyunkwan University School of Medicine, Changwon 51353, Korea
2
Department of Neurology, Samsung Changwon Hospital, Sungkyunkwan University School of Medicine, Changwon 51353, Korea
3
Department of Biostatistics, Samsung Changwon Hospital, Sungkyunkwan University School of Medicine, Changwon 51353, Korea
*
Author to whom correspondence should be addressed.
J. Clin. Med. 2021, 10(18), 4122; https://doi.org/10.3390/jcm10184122
Submission received: 24 August 2021
/
Revised: 3 September 2021
/
Accepted: 10 September 2021
/
Published: 13 September 2021
(This article belongs to the Section Clinical Neurology)
Abstract
:(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.
1. Introduction
Stroke is a major cause of acquired physical disability in adults worldwide [1,2]. Sequelae from stroke generally include motor weakness and cognitive impairment [1,2]. Stroke patients with sequelae may suffer from mental health problems, such as depression, suicidal ideation, and suicide attempt [3,4,5,6,7,8,9].
Mental health concerns for stroke patients have frequently been reported [5,9,10]. Previous studies have found that stroke patients have higher rates of depression and suicidal ideation, and stroke survivors with depression appear to have a higher mortality rate than those without depression [5]. Another study reported that stroke patients living alone, with low education, and low income had a higher risk of suicide attempts [6,8,10].
This nationwide database analysis study using the Korea National Health and Nutrition Examination Survey (KNHANES) aimed to comprehensively evaluate the association between sociodemographic factors and mental health and stroke sequelae. The KNHANES, which includes not only health status but also sociodemographic and economic factors, is an annual cross-sectional survey designed to examine the health and nutritional status of the Korean population [11].
We hypothesized that stroke patients with sequelae were more likely to have poor sociodemographic factors and to suffer from mental health problems than those without sequelae. We aimed to compare sociodemographic factors and mental health between stroke patients with and without sequelae. We also investigated the factors affecting depression in patients with stroke.
2. Materials and Methods
2.1. Study Population
This study was based on data obtained from the 2016–2019 KNHANES. During the study period, 32,379 individuals participated in the KNHANES. Among them, the 569 respondents who answered “yes” to the question “Have you ever been diagnosed with stroke by a clinical physician?” were included in this study. The participants were then divided into two groups based on the question “Are you suffering from stroke?”. Individuals who responded “yes” were classified as stroke patients with sequelae (n = 227), and individuals who responded “no” were classified as stroke patients without sequelae (n = 340).
2.2. Variables
The KNHANES includes well-established questions regarding sociodemographic factors, such as sex, age, height, weight, body mass index (BMI), monthly household income, number of household members, house ownership, employment status, marital status, level of education, smoking status, and alcohol consumption. None of the 569 respondents were excluded, even though many had missing data. Due to the considerable number of missing variables, it would have been impossible to perform chi-square tests if all were excluded. However, there were no differences in general characteristics between those who provided complete responses and those who did not.
BMI was calculated by dividing weight (kg) by height (m2). In the KNHANES, monthly household income is classified into quartiles (1: low, 2 and 3: middle, and 4: high); however, in this study, it was divided into two groups (lower half and upper half). Employment status was divided into either employed or unemployed. For marital status, participants were categorized as married or unmarried, and those who were widowed or divorced were included in the married group. For level of education, participants were classified into elementary school or lower, middle school, high school, or college or higher. Smoking status was divided into two categories: smokers and non-smokers. Alcohol consumption was divided into two categories: drinkers and non-drinkers.
Three dimensions of mental health were investigated: depression, suicidal ideation, and suicide attempts. Respondents who had been diagnosed with depression by a clinical physician were considered to have depression. Suicidal ideation was evaluated using the response to the following question: “Have you thought about committing suicide in the past year?” (yes or no). Suicide attempt was evaluated using the response to the question: “Have you attempted suicide in the past year?” (yes or no).
2.3. Statistical Analysis
All statistical analyses were conducted using SPSS version 22 (IBM Corp., Armonk, NY, USA). The KNHANES data were collected through a representative, stratified, and clustered sampling method. Sociodemographic factors and mental health were compared between stroke patients with and without sequelae, and between stroke patients with and without depression. Categorical variables were analyzed using the chi-square test or Fisher’s exact test. Continuous variables were analyzed using the Student’s t-test or the Mann–Whitney U test. Statistical significance was set at p < 0.05. The collinearity diagnostic check was performed by calculating the variance inflation factors for all independent variables. All variables had a variance factor value of less than 2, indicating that they were not closely correlated. No adjustment was made for multiplicity. A multivariable logistic regression analysis was conducted to evaluate the factors affecting depression in patients with stroke. All variables with a p-value < 0.20 in the univariate analysis were included in the logistic regression analysis.
3. Results
Table 1 shows the general characteristics of the participants diagnosed with stroke during the survey period (2016–2019). A total of 567 subjects from the KNHANES (2016–2019) were included in this study. Slightly over half (53.1%) were male, and the mean age was 65.7 ± 11.9 years. More participants had a low monthly household income (score of 1) than a high income (score of 4) (255/567 (45.0%) vs. 61/567 (10.7%)). Most of the participants were married (96.1%), and depression was observed in 55 of the participants (9.70%).
The characteristics of stroke patients with and without sequelae in the KNHANES (2016–2019) are compared in Table 2. In the group of stroke patients with sequelae, 61.2% (139/227) were male, while 47.6% (162/340) were male in the group without sequelae (p = 0.002). Additionally, more of the patients with sequelae had monthly household incomes in the lower half than those without sequelae (179/227 (78.9%) vs. 229/340 (67.4%), p = 0.005). Fewer of the stroke patients with sequelae owned a house than those without sequelae (137/227 (60.4%) vs. 232/340 (68.2%), p = 0.048). Furthermore, there were more unmarried individuals in the group of stroke patients with sequelae than in the group without sequelae (16/227 (7.05%) vs. 6/340 (1.76%), p < 0.001). Lastly, stroke patients with sequelae were more likely to be smokers than those without sequelae (126/227 (55.5%) vs. 154/340 (45.3%), p = 0.016).
Stroke patients with sequelae had poorer mental health, including depression, suicidal ideation, and suicide attempts, than those without sequelae. Depression was observed more frequently in stroke patients with sequelae than in those without sequelae (30/227 (13.2%) vs. 25/340 (7.35%), p = 0.045). Suicidal ideation and suicide attempts were also observed more frequently in stroke patients with sequelae than in those without sequelae (14/227 (6.17%) vs. 11/340 (3.24%), p = 0.010, and 6/227 (2.64%) vs. 3/340 (0.88%), p = 0.012, respectively).
In Table 3, the characteristics of stroke patients with and without depression in the KNHANES (2016–2019) are compared. There were fewer males in the group of stroke patients with depression than in the group without depression (15/55 (27.3%) vs. 286/512 (55.9%), p < 0.001). Stroke patients with depression had a lower employment rate than those without depression (8/55 (15.5%) vs. 182/512 (35.5%), p < 0.001). Additionally, smokers were observed more frequently in stroke patients without depression than in those with depression (263/512 (51.4%) vs. 17/55 (30.9%), p = 0.002). Lastly, suicidal ideation and suicide attempts were observed more frequently in stroke patients with depression than in those without depression (7/55 (12.7%) vs. 18/512 (3.52%), p = 0.003, and 6/55 (10.9%) vs. 3/512 (0.59%), p < 0.001, respectively).
The multivariable analysis of factors related to depression in stroke patients, which included sex, height, BMI, house ownership, employment status, smoking status, alcohol consumption, and sequelae of stroke, revealed that sex (female) (adjusted odds ratios (OR): 3.878, adjusted 95% confidence interval (CI): 2.060–7.301, p < 0.001), and presence of stroke sequelae (adjusted OR: 2.443, adjusted 95% CI: 1.368–4.364, p = 0.003) were independently associated with depression in stroke patients (Table 4).
4. Discussion
In this nationwide population-based study of stroke patients, we observed sociodemographic differences between stroke patients with and without sequelae. Our results showed that stroke patients with sequelae had poorer sociodemographic factors, such as lower monthly household income, not owning a house, and not being married, than those without sequelae. This study suggests that stroke patients with sequelae have a poorer sociodemographic status than those without sequelae. Our results also showed that the percentage of stroke patients with a monthly household income of 1 (low) was close to 50%, suggesting that stroke patients tended to have relatively low incomes.
Sociodemographic factors may have an influence on the sequelae after stroke because socially disadvantaged patients are less likely to receive appropriate treatments [12,13,14]. The presence of sequelae after stroke may also have an influence on patients’ socioeconomic status [3,13,14]. Since this was a cross-sectional study, no causal conclusions could be drawn. However, to the best of our knowledge, this study is the first to compare sociodemographic factors between stroke patients with and without sequelae using a nationwide survey.
Previous studies have reported that stroke patients have higher rates of depression and suicidal ideation [3,5,6,10]. In our study, we considered sociodemographic factors and mental health problems in stroke patients with and without sequelae using nationwide data and found that stroke patients with sequelae had more mental health issues than those without sequelae. This can therefore be considered a foundational study of the association between sociodemographic factors and mental health problems and the presence of sequelae in stroke patients.
In this study, the proportion of stroke patients diagnosed with depression was 9.70%. Our results also showed that stroke patients with depression had higher rates of sequelae and a lower rate of employment than those without depression. Depression could therefore be linked to physical disability and subsequent unemployment resulting from stroke [9,15,16].
Female sex is known to be an important risk factor for depression in the general population [17]. Previous studies on depression in stroke patients conducted in other countries have reported that the rate of depression does not differ significantly between male and female stroke patients [18]; however, our study showed that female sex was independently associated with depression in stroke patients. This can be partially explained by international and cultural differences among countries.
In this study, a strong association between depression and stroke sequelae was observed. Previous studies have reported that the loss of physical function and independence are strongly associated with depression and suicidal ideation in stroke patients [9,16], which is consistent with our results. This study emphasized the importance of carefully screening for depression and suicidality in stroke patients, especially in those with sequelae and poor sociodemographic factors.
This study also has several limitations. First, knowing the temporal relationship between stroke and mental health problems would be helpful to understand the effect of mental health problems on stroke outcomes and the effect of stroke outcomes on mental health problems. However, given that this was a cross-sectional analysis, it was impossible to draw causal conclusions. Second, although the study included a large sample from a nationwide health survey, most of the data were self-reported. The potential issues associated with self-reported data are label errors, recall bias, and a lack of accuracy. Third, knowing the stroke severity, types of stroke (such as hemorrhagic stroke and ischemic stroke), and specific types of sequelae of stroke (such as hemiparesis, sensory change, aphasia, and cognitive dysfunction) can give us a better understanding of mental health problems after stroke as they relate to such factors. However, KNHANES did not have data on the stroke severity, types of stroke, and types of sequelae of stroke. Only individual-level data on the presence or absence of stroke and sequelae were included, which was a limitation of this study. Fourth, there may be misclassification bias in the classification of this study, such as patients with and without stroke, sequelae of stroke, and mental health problems. Validation studies are needed to estimate the reliability of this classification. Further epidemiologic studies are needed to determine the differences in sociodemographic factors and mental health between stroke patients with and without sequelae and to assess international and cultural differences.
5. Conclusions
Using a large population-based survey, we observed that stroke patients with sequelae had poorer sociodemographic factors and more mental health problems than those without sequelae. We also found that the risk of depression in stroke patients was related to female sex and the presence of sequelae. Our findings suggest that clinicians should carefully screen for depression and suicidality in stroke patients with sequelae, especially in those with poor sociodemographic factors.
Author Contributions
Conceptualization, S.H.K.; methodology, T.M.N. and N.G.K.; software, D.-H.K.; validation, J.H.J.; formal analysis, Y.Z.K. and N.G.K.; investigation, C.W.O.; resources, K.H.K.; data curation, S.H.L.; writing—original draft preparation, C.W.O.; writing—review and editing, S.H.K.; visualization, S.H.K.; supervision, Y.Z.K.; project administration, K.H.K.; funding acquisition, S.H.K. All authors have read and agreed to the published version of the manuscript.
Funding
This research received no external funding.
Institutional Review Board Statement
The study was conducted according to the guidelines of the Declaration of Helsinki, and approved by the Institutional Review Board of Samsung Changwon Hospital, Sungkyunkwan University School of Medicine (SCMC 2021-08-003, date of approval: Aug 23rd, 2021).
Informed Consent Statement
Patient consent was waived by the board.
Conflicts of Interest
The authors declare no conflict of interest.
References
- Broussy, S.; Saillour-Glenisson, F.; García-Lorenzo, B.; Rouanet, F.; Lesaine, E.; Maugeais, M.; Aly, F.; Glize, B.; Salamon, R.; Sibon, I. Sequelae and Quality of Life in Patients Living at Home 1 Year After a Stroke Managed in Stroke Units. Front. Neurol. 2019, 10, 907. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Emberson, J.; Lees, K.R.; Lyden, P.; Blackwell, L.; Albers, G.; Bluhmki, E.; Brott, T.; Cohen, G.; Davis, S.; Donnan, G. Effect of treatment delay, age, and stroke severity on the effects of intravenous thrombolysis with alteplase for acute ischaemic stroke meta-analysis of individual patient data from randomised trials. Lancet 2014, 384, 1929–1935. [Google Scholar] [CrossRef] [Green Version]
- 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, 7, 1–10. [Google Scholar]
- Paolucci, S. Epidemiology and treatment of post-stroke depression. Neuropsychiatr. Dis. Treat. 2008, 4, 145–154. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Yeoh, Y.S.; Koh, G.C.; Tan, C.S.; Tu, T.M.; Singh, R.; Chang, H.M.; De Silva, D.A.; Ng, Y.S.; Ang, Y.H.; Yap, P. Health-related quality of life loss associated with first-time stroke. PLoS ONE 2019, 14, e0211493. [Google Scholar] [CrossRef] [PubMed]
- Chung, J.H.; Kim, J.B.; Kim, J.H. Suicidal ideation and attempts in patients with stroke population-based study. J. Neurol. 2016, 263, 2032–2038. [Google Scholar] [CrossRef] [PubMed]
- Levy, S.A.; Pedowitz, E.; Stein, L.K.; Dhamoon, M.S. Healthcare Utilization for Stroke Patients at the End of Life: Nationally Representative Data. J. Stroke Cerebrovasc. Dis. 2021, 30, 106008. [Google Scholar] [CrossRef] [PubMed]
- Eriksson, M.; Glader, E.L.; Norrving, B.; Asplund, K. Poststroke suicide attempts and completed suicides socioeconomic and nationwide perspective. Neurology 2015, 84, 1732–1738. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Ones, K.; Yilmaz, E.; Cetinkaya, B.; Caglar, N. Quality of life for patients poststroke and the factors affecting it. J. Stroke Cerebrovasc. Dis. 2005, 14, 261–266. [Google Scholar] [CrossRef] [PubMed]
- Yang, Y.; Shi, Y.Z.; Zhang, N.; Wang, S.; Ungvari, G.S.; Ng, C.H.; Wang, Y.L.; Zhao, X.Q.; Wang, Y.J.; Wang, C.X. Suicidal ideation at 1-year post-stroke: A nationwide survey in China. Gen. Hosp. Psychiatry 2017, 44, 38–42. [Google Scholar] [CrossRef] [PubMed]
- Kim, Y. The Korea National Health and Nutrition Examination Survey (KNHANES) status and challenges. Epidemiol. Health 2014, 36, e2014002. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Dalton, S.O.; Steding-Jessen, M.; Jakobsen, E.; Mellemgaard, A.; Østerlind, K.; Schüz, J.; Johansen, C. Socioeconomic position and survival after lung cancer: Influence of stage, treatment and comorbidity among Danish patients with lung cancer diagnosed in 2004–2010. Acta Oncol. 2015, 54, 797–804. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Falkentoft, A.C.; Zareini, B.; Andersen, J.; Wichmand, C.; Hansen, T.B.; Selmer, C.; Schou, M.; Gæde, P.H.; Staehr, P.B.; Hlatky, M.A. Socioeconomic position and first-time major cardiovascular event in patients with type 2 diabetes: A Danish nationwide cohort study. Eur. J. Prev. Cardiol. 2021, zwab065. [Google Scholar] [CrossRef] [PubMed]
- Andersen, J.; Gerds, T.A.; Gislason, G.; Schou, M.; Torp-Pedersen, C.; Hlatky, M.A.; Møller, S.; Madelaire, C.; Strandberg-Larsen, K. Socioeconomic position and one-year mortality risk among patients with heart failure: A nationwide register-based cohort study. Eur. J. Prev. Cardiol. 2020, 27, 79–88. [Google Scholar] [CrossRef] [PubMed]
- Kim, M.; Lee, Y.H. Gender-specific factors related to suicidal ideation among community-dwelling stroke survivors: The 2013 Korean Community Health Survey. PLoS ONE 2018, 13, e0201717. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Bartoli, F.; Pompili, M.; Lillia, N.; Crocamo, C.; Salemi, G.; Clerici, M.; Carrà, G. Rates and correlates of suicidal ideation among stroke survivors: A meta-analysis. J. Neurol. Neurosurg. Psychiatry 2017, 88, 498–504. [Google Scholar] [CrossRef] [PubMed]
- Cole, M.G.; Dendukuri, N. Risk factors for depression among elderly community subjects: A systematic review and meta-analysis. Am. J. Psychiatry 2003, 160, 1147–1156. [Google Scholar] [CrossRef] [PubMed]
- Razmara, A.; Valle, N.; Markovic, D.; Sanossian, N.; Ovbiagele, B.; Dutta, T.; Towfighi, A. Depression Is Associated with a Higher Risk of Death among Stroke Survivors. J. Stroke Cerebrovasc. Dis. 2017, 26, 2870–2879. [Google Scholar] [CrossRef] [PubMed]
Table 1.
General characteristics of the study subjects retrieved from the Korea National Health and Nutrition Examination Survey (KNHANES) (2016–2019).
Table 1.
General characteristics of the study subjects retrieved from the Korea National Health and Nutrition Examination Survey (KNHANES) (2016–2019).
| Variables | Stroke patients (n = 567) | |
|---|---|---|
| Sociodemographic factors | Sex (male) | 301 (53.1%) |
| Age (years) | 65.7 ± 11.9 | |
| Height (cm) | 161.2 ± 9.07 | |
| Weight (kg) | 64.1 ± 11.7 | |
| Body mass index (kg/m2) | 24.6 ± 3.34 | |
| Monthly household income | ||
| 1 (low) | 255 (45.0%) | |
| 2 (middle) | 153 (27.0%) | |
| 3 (middle) | 98 (17.3%) | |
| 4 (high) | 61 (10.7%) | |
| Number of household members | ||
| 1 | 128 (22.6%) | |
| 2 | 254 (44.8%) | |
| 3 | 102 (18.0%) | |
| 4 | 43 (7.58%) | |
| ≥5 | 40 (7.05%) | |
| House ownership | 369 (65.1%) | |
| Employment status (employed) | 190 (33.5%) | |
| Marital status (married) | 545 (96.1%) | |
| Level of education | ||
| Elementary school or lower | 285 (50.3%) | |
| Middle school | 98 (17.3%) | |
| High school | 123 (21.7%) | |
| College or higher | 61 (10.8%) | |
| Smoking status (smoker) | 280 (49.4%) | |
| Alcohol consumption (drinker) | 455 (80.2%) | |
| Mental health | Depression | 55 (9.70%) |
| Suicidal ideation | 25 (4.41%) | |
| Suicide attempts | 9 (1.59%) | |
Table 2.
A comparison of stroke patients with and without sequelae retrieved from the Korea National Health and Nutrition Examination Survey (KNHANES) (2016–2019).
Table 2.
A comparison of stroke patients with and without sequelae retrieved from the Korea National Health and Nutrition Examination Survey (KNHANES) (2016–2019).
| Variables | Sequelae of Stroke | p-Value | ||
|---|---|---|---|---|
| Present (n = 227) | Absent (n = 340) | |||
| Sociodemographic factors | Sex (male) | 139 (61.2%) | 162 (47.6%) | 0.002 |
| Age (years) | 64.2 ± 12.6 | 66.7 ± 11.2 | 0.468 | |
| Height (cm) | 161.1 ± 9.22 | 159.5 ± 8.85 | 0.040 | |
| Weight (kg) | 63.7 ± 11.8 | 63.1 ± 11.0 | 0.551 | |
| Body mass index (kg/m2) | 24.4 ± 3.28 | 24.8 ± 3.48 | 0.279 | |
| Monthly household income | 0.005 | |||
| Lower half | 179 | 229 | ||
| Upper half | 48 | 111 | ||
| Number of household members | 0.500 | |||
| 1 | 54 | 74 | ||
| 2 | 106 | 148 | ||
| 3 | 35 | 67 | ||
| 4 | 18 | 25 | ||
| ≥5 | 14 | 26 | ||
| House ownership | 137 (60.4%) | 233 (68.5%) | 0.048 | |
| Employment status (employed) | 65 (28.6%) | 125 (36.8%) | 0.151 | |
| Marital status (unmarried) | 16 (7.05%) | 6 (1.76%) | <0.001 | |
| Level of education | 0.221 | |||
| Elementary school or lower | 108 | 177 | ||
| Middle school | 35 | 63 | ||
| High school | 57 | 66 | ||
| College or higher | 25 | 36 | ||
| Smoking status (smoker) | 126 (55.5%) | 154 (45.3%) | 0.016 | |
| Alcohol consumption (drinker) | 184 (81.1%) | 271 (79.7%) | 0.121 | |
| Mental health | Depression | 30 (13.2%) | 25 (7.35%) | 0.045 |
| Suicidal ideation | 14 (6.17%) | 11 (3.24%) | 0.010 | |
| Suicide attempts | 6 (2.64%) | 3 (0.88%) | 0.012 | |
Table 3.
A comparison of the study subjects with and without depression retrieved from the Korea National Health and Nutrition Examination Survey (KNHANES) (2016–2019).
Table 3.
A comparison of the study subjects with and without depression retrieved from the Korea National Health and Nutrition Examination Survey (KNHANES) (2016–2019).
| Variables | Depression | p-Value | ||
|---|---|---|---|---|
| Present (n = 55) | Absent (n = 512) | |||
| Sociodemographic factors | Sex (male) | 15 (27.3%) | 286 (55.9) | <0.001 |
| Age (years) | 68.0 ± 10.6 | 68.1 ± 10.8 | 0.946 | |
| Height (cm) | 157.8 ± 9.00 | 160.4 ± 9.00 | 0.044 | |
| Weight (kg) | 63.0 ± 9.95 | 63.4 ± 11.5 | 0.791 | |
| Body mass index (kg/m2) | 25.3 ± 3.43 | 24.6 ± 3.40 | 0.142 | |
| Monthly household income | 0.814 | |||
| Lower half | 41 | 367 | ||
| Upper half | 14 | 145 | ||
| Number of household members | 0.292 | |||
| 1 | 20 | 108 | ||
| 2 | 20 | 234 | ||
| 3 | 7 | 95 | ||
| 4 | 2 | 41 | ||
| ≥5 | 6 | 34 | ||
| House ownership | 30 (54.5%) | 340 (66.4%) | 0.100 | |
| Employment status (employed) | 8 (14.5%) | 182 (35.5%) | <0.001 | |
| Marital status (unmarried) | 2 (3.6%) | 20 (3.9%) | 1.000 | |
| Smoking status (smoker) | 17 (30.9%) | 263 (51.4%) | 0.002 | |
| Alcohol consumption (drinker) | 39 (70.9%) | 416 (81.3%) | 0.053 | |
| Sequelae of stroke | 30 (54.5%) | 197 (38.5%) | 0.045 | |
| Mental health | Suicidal ideation | 7 (12.7%) | 18 (3.52%) | 0.003 |
| Suicide attempts | 6 (10.9%) | 3 (0.59%) | <0.001 | |
Table 4.
Multivariable logistic regression analysis of the factors affecting depression in stroke patients retrieved from the Korea National Health and Nutrition Examination Survey (KNHANES) (2016–2019).
Table 4.
Multivariable logistic regression analysis of the factors affecting depression in stroke patients retrieved from the Korea National Health and Nutrition Examination Survey (KNHANES) (2016–2019).
| Factors | Adjusted OR | Adjusted 95% CI | p-Value |
|---|---|---|---|
| Sex (female) | 3.878 | 2.060–7.301 | <0.001 |
| Sequelae of stroke | 2.443 | 1.368–4.364 | 0.003 |
OR: Odds ratio, CI: Confidence interval.
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Oh, C.W.; Lee, S.H.; Nam, T.M.; Jang, J.H.; Kim, Y.Z.; Kim, K.H.; Kim, D.-H.; Ko, N.G.; Kim, S.H. Comparative Analysis of Stroke Patients with and without Sequelae: A Cross-Sectional Analysis Using the KOREA National Health and Nutrition Examination Survey (2016–2019). J. Clin. Med. 2021, 10, 4122. https://doi.org/10.3390/jcm10184122
AMA Style
Oh CW, Lee SH, Nam TM, Jang JH, Kim YZ, Kim KH, Kim D-H, Ko NG, Kim SH. Comparative Analysis of Stroke Patients with and without Sequelae: A Cross-Sectional Analysis Using the KOREA National Health and Nutrition Examination Survey (2016–2019). Journal of Clinical Medicine. 2021; 10(18):4122. https://doi.org/10.3390/jcm10184122
Chicago/Turabian StyleOh, Chi Woong, Sang Hyuk Lee, Taek Min Nam, Ji Hwan Jang, Young Zoon Kim, Kyu Hong Kim, Do-Hyung Kim, Nak Gyeong Ko, and Seung Hwan Kim. 2021. "Comparative Analysis of Stroke Patients with and without Sequelae: A Cross-Sectional Analysis Using the KOREA National Health and Nutrition Examination Survey (2016–2019)" Journal of Clinical Medicine 10, no. 18: 4122. https://doi.org/10.3390/jcm10184122
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