International Journal of
Environmental Research
and Public Health
Article
Analysis of Factors Affecting Depression in Older Adults in
South Korea
Ah-Ram Kim
1,†
, Jin-Hyuck Park
2
and Hae Yean Park
3,
*
,†
Citation: Kim, A.-R.; Park, J.-H.;
Park, H.Y. Analysis of Factors
Affecting Depression in Older Adults
in South Korea. Int. J. Environ. Res.
Public Health 2021, 18, 9887. https://
doi.org/10.3390/ijerph18189887
Academic Editors: Keun-Ho Ryu and
Nipon Theera-Umpon
Received: 26 August 2021
Accepted: 18 September 2021
Published: 20 September 2021
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1
Department of Occupational Therapy, Graduate School, Yonsei University, Wonju 26493, Korea;
aramkim495@gmail.com
2
Department of Occupational Therapy, Soonchunhyang University, Asan 31538, Korea; roophy@naver.com
3
Department of Occupational Therapy, College of Software and Digital Healthcare Convergence,
Yonsei University, Wonju 26493, Korea
* Correspondence: haepark@yonsei.ac.kr
† Current Address: Department of Occupational Therapy, Yonsei University, Wonju 26493, Korea.
Abstract: Objective:
This study aimed to analyze the factors affecting depression among South
Korean middle-aged and older adults using data from the Korean Longitudinal Study of Aging.
Methods:
We analyzed data regarding demographic characteristics, lifestyle, quality of life, cognitive
level, and depression. Cognitive level and depression were evaluated using the Korean-Mini-Mental
Status Examination and Center for Epidemiological Studies Depression Scale, respectively.
Results:
Depression was correlated with age, gender, residential area, level of education, alcohol intake,
regular exercise, life satisfaction, and cognitive level, but not smoking. Furthermore, depression was
highly affected by age, residential area, regular exercise, life satisfaction, and cognitive level, with a
prediction accuracy of 80.26% achieved through machine learning analysis.
Conclusions:
Various
factors are associated with depression in middle-aged and older adults. Therefore, multifaceted
interventions for preventing depression in these age groups are required.
Keywords:
depression; Korean Longitudinal Study of Aging (KLoSA); machine learning; older adult
1. Introduction
South Korea is experiencing an increasingly aged population, with 15.8% of the
population aged
≥
65 years as of 2020 [
1
]. Currently, the average life expectancy of South
Koreans is 83.2 years (2020), which is expected to rise to 86.8 years after two decades [
2
]. In
2019, the life satisfaction of South Koreans according to age group was found to be lowest
among individuals in their 60s (the scores out of 10 points for every age group were as
follows: teens and 20s, 6.0 points; 30s, 6.1 points; 40s, 5.9 points; 50s, 6.1 points; and 60s,
5.8 points) [
3
]. A study on happiness by life cycle in Japan and South Korea that used data
from the East Asian Social Survey reported a negative correlation between happiness and
age [
4
]. South Korea is about to become a super-aged society. Therefore, there is a need to
actively seek intervention measures for improving the quality of life in older adults at the
social level and to focus on providing necessary resources.
Various factors affect the quality of life or satisfaction in older adults. Life satisfac-
tion is not an objective condition; rather, it is a combination of an internal and subjective
process [
5
]. Therefore, there has been growing interest in factors associated with life satis-
faction, especially psychological or personality factors, including depression, anxiety, and
neurosis [
6
]. Among the psychological factors, depression has negative effects, including
increasing the socioeconomic burden, reducing the quality of life among older adults, and
increasing the rates of morbidity and mortality [7].
Depression is a universal human emotion characterized by a continuous variation
that ranges from mild to abnormal levels [
8
]. However, depression is more common in
late stages of life, with 20–25% of older adults experiencing depression [
9
]; this decreases
Int. J. Environ. Res. Public Health 2021, 18, 9887. https://doi.org/10.3390/ijerph18189887 https://www.mdpi.com/journal/ijerph
