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

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

Article information

Korean J Health Promot. 2014;14(4):162-171
Publication date (electronic) : 2014 January 20
doi : https://doi.org/10.15384/kjhp.2014.14.4.162
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 2014 October 24; Accepted 2014 November 27.

Abstract

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.

Figure 1.

Regression model of variables by SEM (standardized regression weights)

Differences of variables according to general characteristics of study participantsa

Correlations between ADL, social support, depression, and suicidal ideationa

Variables influencing suicidal ideation of subjectsa

Standardized parameter statistics in hypothetical modela (regression weights)

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Article information Continued

Figure 1.

Regression model of variables by SEM (standardized regression weights)

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.