Depression status and influencing factors of empty-nest elderly based on structural equation model
10.16462/j.cnki.zhjbkz.2019.10.005
- Author:
Ya-qing XUE
1
;
Chi-chen ZHANG
;
Hui-ning ZHAO
;
Xiao ZHENG
;
Yuan CAI
Author Information
1. School of Management, Shanxi Medical University, Taiyuan 030001, China
- Publication Type:Research Article
- Keywords:
Empty-nest elderly;
Depression;
Influencing factors;
Structural equation model
- From:
Chinese Journal of Disease Control & Prevention
2019;23(10):1181-1185
- CountryChina
- Language:Chinese
-
Abstract:
Objective To clarify the depression status of empty-nest elderly in Shanxi Province, to explore the related influencing factors by structural equation model, and to provide scientific basis for the prevention and intervention of depression for empty nesters. Methods A questionnaire survey was conducted among 4 901 empty-nest elderly in Shanxi Province by self-rating depression scale and general situation questionnaire, and the model was established. Results The prevalence of depressive symptoms among empty nesters in Shanxi Province was 64.21%. The model demonstrated that health status had a direct impact on depressive symptoms (P=0.028), the total effect was -0.978; the effect of economic status on depressive symptoms was 0.086 (P=0.030), and social function had no significant impact on depressive symptoms (P=0.173), which could affect depressive symptoms through affecting health status and economic status. There was a significant correlation between the three latent variables (P<0.05). Health status had the strongest correlation with social function (r=0.942), followed by economic status (r=0.718), and the correlation between social function and economic status was 0.683. Conclusions In this research, most of the empty-nest elderly suffer from depressive symptoms. Health status is the most direct and important influencing factor of depressive symptoms in empty nesters. Social function affects depressive symptoms through influencing health status and economic status.
