Case Control Study
Copyright ©The Author(s) 2021. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Psychiatr. Dec 19, 2021; 11(12): 1314-1327
Published online Dec 19, 2021. doi: 10.5498/wjp.v11.i12.1314
Developing a nomogram for predicting the depression of senior citizens living alone while focusing on perceived social support
Haewon Byeon
Haewon Byeon, Department of Medical Big Data, Inje University, Gimhae, 50834, Gyeonsangnamdo, South Korea
Author contributions: Byeon H was designed the study, involved in data interpretation, preformed the statistical analysis, and assisted with writing the article.
Supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (NRF-2018R1D1A1B07041091, NRF-2021S1A5A8062526).
Institutional review board statement: The study was approved by the Research Ethics Review Board of the National Biobank of Korea (No. KBN-2019-005) and the H University (No. 20180042).
Informed consent statement: All patients gave informed consent.
Conflict-of-interest statement: No benefits in any form have been received or will be received from a commercial party related directly or indirectly to the subject of this article.
Data sharing statement: Technical appendix, statistical code from the corresponding author at bhwpuma@naver.com.
STROBE statement: The authors have read the STROBE statement—checklist of items, and the manuscript was prepared and revised according to the STROBE statement—checklist of items.
Open-Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Haewon Byeon, DSc, PhD, Associate Professor, Director, Department of Medical Big Data, Inje University, 197, Inje-ro, Gimhae, 50834, Gyeonsangnamdo, South Korea. bhwpuma@naver.com
Received: May 23, 2021
Peer-review started: May 23, 2021
First decision: July 14, 2021
Revised: July 18, 2021
Accepted: November 3, 2021
Article in press: November 3, 2021
Published online: December 19, 2021
Abstract
BACKGROUND

Although the number of senior citizens living alone is increasing, only a few studies have identified factors related to the depression characteristics of senior citizens living alone by using epidemiological survey data that can represent a population group.

AIM

To evaluate prediction performance by building models for predicting the depression of senior citizens living alone that included subjective social isolation and perceived social support as well as personal characteristics such as age and drinking.

METHODS

This study analyzed 1558 senior citizens (695 males and 863 females) who were 60 years or older and completed an epidemiological survey representing the South Korean population. Depression, an outcome variable, was measured using the short form of the Korean version CES-D (short form of CES-D).

RESULTS

The prevalence of depression among the senior citizens living alone was 7.7%. The results of multiple logistic regression analysis showed that the experience of suicidal urge over the past year, subjective satisfaction with help from neighbors, subjective loneliness, age, and self-esteem were significantly related to the depression of senior citizens living alone (P < 0.05). The results of 10-fold cross validation showed that the area under the curve of the nomogram was 0.96, and the F1 score of it was 0.97.

CONCLUSION

It is necessary to strengthen the social network of senior citizens living alone with friends and neighbors based on the results of this study to protect them from depression.

Keywords: Senior citizens living alone, Nomogram, Depression, Risk factor, Perceived social support, Subjective social isolation

Core Tip: In this study, the significant predictors of depression of the senior citizens living alone were the experiences of suicidal urge over the past year, dissatisfaction with help from neighbors, subjective loneliness, age, and low self-esteem. The results of this study implied that it is necessary to develop a support system customized for subjects to strengthen the relation network for preventing depression in senior citizens living alone so that they can receive actual support (reinforced qualitative network) from acquaintances such as neighbors rather than the frequency of physical contact (reinforced quantitative network).