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Lee and Lee: Structural Equation Modeling of Suicidal Ideation and Associated Factors among Elderly Women in Korea
Original Article

Korean J Health Promot 2014;14(4):162-171.

Published online: 20 January 2014

DOI: https://doi.org/10.15384/kjhp.2014.14.4.162

Structural Equation Modeling of Suicidal Ideation and Associated Factors among Elderly Women in Korea

Hung Sa Lee1, Dohyun Lee2,

1Department of Nursing Science, College of Health Science, Sun Moon University, Asan, Korea

2PhD student, School of Public Health, Indiana University Bloomington, Bloomington, IN, USA

Corresponding author：Dohyun Lee, PhD student School of Public Health, Indiana University Bloomington, 1025 E. 7th Street, SPH 192, Indiana University, Bloomington, IN, USA Tel: +1-812-327-4525, Fax: +1-812-327-4525 E-mail: dohylee@indiana.edu

Received 24 October 2014       Accepted 27 November 2014

Copyright © 2014 The Korean Society of Health Promotion and Disease Prevention

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Background

Although the suicide rate in Korea is the highest in the world, only limited studies have been done on suicide and its associated factors. In this regard, we studied a conceptual model and the relationships and interactions of activity of daily living (ADL), social support, depression, and suicidal ideation among elderly women in Korea.

Methods

A cross-sectional descriptive study, subjects included 194 community-dwelling elderly women. Their ADL, multi-dimensional scale of perceived social support (MSPSS), depression, and suicidal ideation (SI) were examined. The t-test, ANOVA test, Pearson's correlation coefficient, multiple regression analysis, and structural equation modeling were utilized in data analysis.

Results

There were significant correlations between SI and economic status, social support, and depression. Depression was correlated with not only SI but also ADL (r=0.195, P=0.006) and social support (r=-0.337, P<0.001). Absolute fit indices demonstrated that the research model had a good model fit. There were significant factor loading values from depression to SI (standardized estimate=0.157, P=0.023) and from social support to SI (standardized estimate=-0.308, P<0.001). There were two indirect effects from social support to SI and from ADL to SI. The mediating factor of these two indirect effects was depression.

Conclusions

Suicidal ideation in the elderly needs to be prevented; and more attention should be given to this end. Social support programs encouraging family participation are greatly effective in prevention of senior citizens' suicidal ideation.

Keywords: Suicidal ideation, Social support, Depression, Aged

References

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Figure 1.
Regression model of variables by SEM (standardized regression weights)
kjhp-14-162f1.tif
Table 1.
Differences of variables according to general characteristics of study participantsa
Characteristics N ADL SS Dep SI
Age, y 77.50 (±5.84)        
 65–74 54 (27.8) 7.33 (±1.71) 4.03 (±0.99) 4.59 (±3.29) 5.68 (±1.51)
 75 & over 140 (72.8) 7.52 (±1.79) 3.90 (±0.99) 5.91 (±4.18) 5.92 (±1.86)
 t (P)b   –0.66 (0.508) 0.77 (0.442) 2.31 (0.022) –0.83 (0.407)
Marital status
 Married 98 (50.5) 7.67 (±2.23) 3.89 (±0.97) 5.41 (±4.05) 5.83 (±1.57)
 Bereaved 96 (49.5) 7.26 (±1.06) 3.99 (±1.02) 5.67 (±3.95) 5.87 (±1.96)
 t (P)   1.64 (0.102) –0.69 (0.489) –0.45 (0.653) –0.15 (0.881)
Education level
 No education 96 (49.5) 7.78 (±2.38)A 3.83 (±1.07) 6.47 (±4.18)A 5.82 (±1.67)
 Elementary school 85 (43.8) 7.18 (±0.69)B 4.00 (±0.91) 4.72 (±3.69)B 5.85 (±1.85)
 Junior high school 13 (6.7) 7.00 (±0.01)C 4.32 (±0.88) 4.00 (±2.91)B 6.07 (±2.10)
 F (P)   3.09 (0.047) 1.60 (0.204) 5.61 (0.004) 0.11 (0.890)
    A>B>C   A>B  
Economic status
 Low 54 (27.8) 7.77 (±2.27) 3.48 (±1.10)A 8.03 (±3.85)A 6.83 (±2.36)A
 Middle 109 (56.2) 7.38 (±1.59) 4.15 (±0.92)B 4.74 (±3.83)B 5.47 (±1.38)B
 High 31 (16.0) 7.22 (±1.25) 3.98 (±0.79)C 4.03 (±2.79)C 5.48 (±1.06)B
 F (P)   0.36 (0.698) 8.72 (<0.001) 17.44 (<0.001) 12.73 (<0.001)
      A<B A<B<C A<B
Living together
 Alone 87 (44.8) 7.37 (±1.35) 3.95 (±0.97) 6.02 (±4.13) 5.79 (±1.74)
 Spouse 63 (32.5) 7.77 (±2.55) 4.01 (±1.02) 5.44 (±3.83) 5.76 (±1.68)
 Children 44 (22.7) 7.20 (±0.82) 3.82 (±1.01) 4.75 (±3.88) 6.11 (±1.96)
 F (P)   1.57 (0.209) 0.48 (0.615) 1.52 (0.221) 0.60 (0.548)
Health status
 Bad 103 (53.1) 7.74 (±2.23) 3.86 (±1.03) 6.21 (±4.20)A 6.01 (±1.90)
 Middle 48 (24.7) 7.12 (±0.73) 4.14 (±0.95) 5.10 (±3.61)B 5.47 (±1.35)
 Good 43 (22.1) 7.18 (±1.07) 3.88 (±0.93) 4.44 (±3.65)B 5.88 (±1.82)
 F (P)   2.79 (0.064) 1.39 (0.251) 3.45 (0.034) 1.53 (0.219)
        A>B  
Living area
 Urban 41 (21.1) 7.09 (±0.37) 3.71 (±0.98) 5.19 (±3.45) 5.85 (±1.85)
 Rural 153 (78.9) 7.56 (±1.96) 4.00 (±0.99) 5.64 (±4.13) 5.85 (±1.76)
 t (P)   –2.77 (0.006) –1.61 (0.107) –0.63 (0.528) –0.08 (0.994)
Working
 No 99 (51.0) 7.58 (±1.94) 3.91 (±1.07) 6.36 (±4.23) 5.98 (±2.00)
 Yes 95 (49.0) 7.34 (±1.55) 3.97 (±0.91) 4.70 (±3.56) 5.71 (±1.49)
 t (P)   –0.94 (0.349) 0.38 (0.700) –2.94 (0.004) –1.07 (0.238)
 Total 194 (100) 7.46 (±1.76) 3.94 (±0.99) 5.54 (±3.99) 5.85 (±1.77)

Abbreviations: ADL, activity of daily living; SS, social support; Dep, depression; SI, suicidal ideation.

a Values are presented as mean±SD or N (%) unless otherwise indicated.

b Calculated by t-test or ANOVA test and Sheffe test.

Table 2.
Correlations between ADL, social support, depression, and suicidal ideationa
Variables Education Economic status Health status ADL SS Dep SI
Education 1            
Economic status 0.031 0.673 1          
Health status 0.273 <0.001 0.270 <0.001 1        
ADL –0.133 0.064 –0.100 0.165 –0.143 0.047 1      
SS 0.068 0.345 0.197 0.006 0.026 0.724 –0.055 0.445 1    
Dep –0.176 0.014 –0.363 <0.001 –0.180 0.012 0.195 0.006 –0.337 <0.001 1  
SI 0.104 0.150 –0.280 <0.001 –0.051 0.484 0.056 0.441 –0.393 <0.001 0.289 <0.001 1

Abbreviations: ADL, activity of daily living; SS, social support; Dep, depression; SI, suicidal ideation.

a Assessed by Pearson correlation coefficient (controlled age).

Table 3.
Variables influencing suicidal ideation of subjectsa
Predictor Β SE β t P
(constant) 4.57 2.10   2.17 0.031
Age 0.04 0.02 0.14 1.81 0.071
Economic status –0.45 0.18 –0.17 –2.45 0.015
Education 0.51 0.21 0.18 2.42 0.016
ADL 0.01 0.06 0.01 0.20 0.837
SS –0.04 0.01 –0.32 –4.67 <0.001
Dep 0.06 0.03 0.14 2.01 0.046
R2=0.245, Adj R2=0.221, F=10.12, P<0.001

Abbreviations: SE, standard error; ADL; activity of daily living; SS, social support; Dep, depression; Adj R2, adjusted R square.

a Calculated by multiple regression analysis.

Table 4.
Standardized parameter statistics in hypothetical modela (regression weights)
Path of variables     Standardized estimate S.E. C.R. P Label Direct effect Indirect effect
Dep ← SS –0.337 0.062 –4.847 <0.001 par_6 –0.337c 0.000
Dep ← ADL 0.190 0.150 2.850 0.004 par_7 0.190c 0.000
Friend support ← SS 0.927         0.927 0.000
Neighbor support ← SS 0.943 0.051 19.461 <0.001 par_1 0.943c 0.000
Family support ← SS 0.734 0.045 12.989 <0.001 par_2 0.734c 0.000
SI ← Dep 0.157 0.031 2.276 0.023 par_3 0.157b 0.000
SI ← ADL 0.003 0.064 0.052 0.958 par_4 0.003 0.030
SI ← SS –0.308 0.029 –4.184 <0.001 par_5 –0.308c –0.053
e10 ↔ d2 –0.296 0.307 –3.766 <0.001 par_8    

Abbreviations: S.E., standard error; C.R., critical ratio; Dep, depression; ADL; activity of daily living; SS, social support; SI, suicidal ideation.

a Calculated by structural equation model analysis.

b P<0.05.

c P<0.01.

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