In many countries, including Korea, low birth rates and aging occur simultaneously. In particular, although the total population of Korea is steadily decreasing due to low birth rate, the proportion of older adults is rapidly increasing due to the development of medical technology (National Indicator System, 2020). In 2019, the proportion of Korean older adults was 14.9% and is expected to reach 20.3% in 2025 (Korean Statistical Information Services, 2020). Moreover, in Korea, the aging index continues to rise, increasing from 67.2% in 2010 to 129% in 2020, which is also high compared to Organisation for Economic Cooperation and Development countries (International Statistical Yearbook, 2019).
As aging emerged as a serious social problem, concerns about older adults who live alone have also received attention. This concern arises from the fact that the proportion of these older adults has increased from 16% in 2000 to 19.4% in 2018 (National Indicator System, 2020). Older adults who live alone are more likely to experience loneliness and alienation than those living with family (National Indicator System, 2020; Victor et al., 2002), and it is more difficult for them to seek help if they experience physical and mental illness (Kim, 2009). According to the National Survey of Older Koreans (2017), 21.4% of older adults living alone reported feelings of psychological anxiety and loneliness compared to 4.8% of older adult couples (Yeh & Lo, 2004). Moreover, 30.2% of older adults living alone experienced depressive symptoms compared to 16.4% and 21.7% of older adult couples and households with children, respectively (Chou & Chi, 2000; Korean Institute for Health and Social Affairs [KIHSA], 2017).
Depression is one of the major risk factors affecting quality of life and successful aging. As aging progresses, physical function decreases and the likelihood of experiencing physical illness increases. These characteristics of old age can have a significant impact on depression in older adults (Hamer et al., 2011; Shin et al., 2017). In particular, older adults who live alone may be more vulnerable to depression than those living with family due to loneliness and lack of social support (Cacioppo et al., 2006; van Winkel et al., 2017).
Health problems of older adults can have a negative effect on their psychological and emotional state (Swami et al., 2007). Several studies have shown that health problems of older adults are positively related to depression (Horowitz et al., 2003; Lenze et al., 2001). Specifically, chronic diseases (Cuijpers, 2001; Perrin et al., 2017), rheumatoid arthritis (Kojima et al., 2009), and stroke (Park et al., 2011) were found to be related to depression. Some studies have argued that perceived health status relates more to depression in older adults than objective health conditions (Leibson et al., 1999; Wolinsky et al., 1988). Therefore, it is necessary to compare the relative influence of objective physical diseases and perceived health conditions on depression.
Physical function is also a major factor affecting depression in older adults. As people age, physical functions naturally decline, and as a result, cause difficulties in their daily lives (Castaneda-Sceppa et al., 2010). Activities of daily living (ADL) and instrumental ADL (IADL) refer to physical functions that older adults should engage in to maintain their independence (Jennifer & Lo, 2004). Many studies have identified an association between decreased physical function and depression (Hamer et al., 2011; Lenze et al., 2001; Turvey et al., 2009).
Thus, physical disease and deterioration of physical function are major risk factors for depression in older adults who live alone. Therefore, it is necessary to understand the variables that mitigate the effects of these risk factors to prevent depression in old age. Social activities might be a significant variable for prevention of depression in older adults who live alone. Social activities may be an effective way to reduce loneliness and expand the social support systems of older adults (Routasalo et al., 2009). Various forms of behavior and thoughts occur in interactions with other individuals (Tropman & Markson, 1983), including social gatherings, school reunions, cultural and sports activities, religious activities, and participation in politics (Lee, 2009; Soubelet, 2013).
Social activity can increase self-efficiency (Perkins et al., 2008) and alleviate depression (Croezen et al., 2015; Holtfreter et al., 2017; Solomonov et al., 2019). They can contribute to the prevention of depression by enabling older adults to experience productivity and life satisfaction by sharing their knowledge and experiences with the community (Gilmour, 2012). However, previous studies have focused on social support (e.g., family support) rather than social participation. In particular, there is lack of understanding of the types of social activities that are more closely related to preventing and reducing depression in older adults.
Finally, among sociodemographic factors related to depression in older adults who live alone, gender has shown a consistent relationship with depression (Tiedt, 2010). The older the person, the more likely depressive symptoms exist (Glaesmer et al., 2011; Horowitz, 2003), and the higher the educational and economic levels, the less severe the depressive symptoms (Glaesmer et al., 2011; Shin et al., 2017). In addition, religion provides emotional support for older adults and may reduce the level of depression for those living alone (Sohn, 2008).
The current study aimed to test the associations among physical illness, physical function, social activity, and depression in older adults who live alone. In particular, the main purpose of the study was to assess the types of social activities that are negatively related to depression in older adults who live alone.
Data from the 2017 National Survey of Older Koreans (KIHSA, 2017) were used in the current study. The survey was performed on 10,299 people (including 226 proxy responses), with 4,375 (42.5%) men and 5,924 (57.5%) women aged ≥65 years (mean = 74.1, SD = 6.7 years) residing in 17 cities and provinces from June 12, 2017 to August 28, 2018. Only 2,258 older adults (mean age = 75.9, SD = 6.8 years; male, n = 420; female, n = 1,838) who live alone were selected for analysis in this study. Those selected were listed under the “type of senior citizen household” question and were older adults with non-cohabitating surviving children. Substitute responses were excluded. The current study did not require Institutional Review Board approval because it used freely available public data.
Sociodemographic Variables. Sociodemographic variables included gender, age, educational level, religion, and total household income. Gender was coded as 0 for males and 1 for females. After confirming that there were no older adults with an educational level higher than university, the levels were classified as no formal education (illiterate), no formal education (literate), elementary school, middle school, and high school or higher. Level of education was coded from 1 for no formal education (illiterate) to 5 for high school or higher. Religion was coded as 1 for participation and 0 for non-participation. Gross household income was coded as 1 for lowest income quintile and 4 for highest income quintile.
Health-Related Variables. Objective health conditions included a physician's diagnosis of stroke, diabetes, angina, myocardial infarction, osteoporosis, or rheumatoid arthritis (yes = 1, no = 0). Perceived health assessments were scored between 1 (not very healthy) and 5 (very healthy). A higher total score indicated better perceived health conditions.
Physical Function. The Korean Instrumental Activities of Daily Living (K-IADL) scale by Won et al. (2002) was used to measure physical function, which was developed to suit Korean culture. The measure comprises 10 categories: personal grooming; household chores; food preparation; laundry; taking medicine at the prescribed time; money management; traveling short distances; shopping, paying money, and getting back change; making and receiving calls; and using transportation. Seven of the 10 questions were scored from 1 (need help completely) to 3 (completely independent), and the remaining three items were scored from 1 (needhelp completely) to 4 (completely independent). The higher the total score, the better the physical function.
Social Activity. To measure social activities, participation in clubs, social gatherings, and political and social groups (0 = non-participation, 1 = participation), as well as the frequency of visits and contact with children living separately in the past 1 year, were measured. The frequency of visits and contact was scored from 0 (hardly any visits or contacts) to 7 (almost every day [i.e., >4 times per week]). When considering the frequency of visits and contact with children living separately, those with the most frequency of contact with children were included in this study.
Depressive Symptoms. The Geriatric Depression Scale (GDS) Short-Form developed by Sheikh and Yesavage (1985) was used to measure depression. The scale comprises 15 questions, with responses of yes or no. Sample questions included: “Are you satisfied with your life?”; “Do you feel your life is empty?”; “Do you often feel helpless?”; “Do you feel that your situation is hopeless?”; and “Are you afraid that something bad is going to happen to you?” Total score ranges from 0 to 15, where 0 to 4 indicates no depression, 5 to 8 indicates mild depression, 9 to 11 indicates moderate depression, and 12 to 15 indicates severe depression. Cronbach's alpha for the GDS was 0.895 in the current study.
Data were analyzed using SPSS version 24. Participant demographics were analyzed using descriptive statistics. The relationship between symptoms of depression, health status, physical function, and social activity of older adults who live alone was analyzed using Pearson's correlation coefficient. Hierarchical regression analysis was performed to identify the effect of predictors on depression of older adults who live alone and the relative influence of the variables. The first step involved demographic variables and the second step involved health-related variables and physical function. The final step involved the frequency of visits and contact with children living separately and the effect of willingness to participate in social activities.
Participants' demographic variables are shown in Table 1. Mean age of participants was 75.9 years (SD = 6.8 years). The proportion of women (82%) was more than four times that of men (18%). There were 626 (28%) elementary school graduates. Moreover, 65.7% of participants were religious and 34.3% were not religious.
Participant Demographics (N = 2,258)
Correlations Among Variables
The results of Pearson's correlation analysis to verify the correlation among variables are shown in Table A (available in the online version of this article). Depression was positively correlated with age, stroke, angina and myocardial infarction, diabetes, osteoarthritis, and rheumatoid arthritis. However, depression was negatively correlated with educational level, religious status, income quintile, perceived health status, IADL, frequency of visits and contacts with children living separately, and willingness to participate in social clubs and gatherings.
The results of Pearson correlation analysis between variables
Hierarchical Multiple Regression
In the first step, gender (β = −0.048, p < 0.05), education (β = −0.062, p < 0.01), income quintile (β = −0.095, p < 0.001), and religion (β = −0.044, p < 0.05) had a negative impact on depressive symptoms in Korean older adults who live alone (Table B, available in the online version of this article). These findings indicate that the level of depression is high for older adults who do not follow any religion and have low levels of education and income. The level of depression among male older adults living alone is higher than among female older adults. Age did not impact depressive symptoms.
Hierarchical regression analysis
In the second step, perceived health status (β = −0.328, p < 0.001) and IADL (β = −0.161, p < 0.001) had a negative effect on depressive symptoms, meaning the better the perceived health status and physical function, the lower the level of depression. On the other hand, stroke, angina and myocardial infarction, diabetes, osteoarthritis, or rheumatoid arthritis did not impact depressive symptoms. Perceived and objective health status and physical function explained 19% of depressive symptoms.
In the third step, the frequency of visits and contact with children living separately (β = −0.095, p < 0.001) and willingness to participate in social gatherings (β = −0.128, p < 0.001) had a negative influence on depressive symptoms. Thus, older adults living alone who participated in social gatherings and had more frequent contacts and visits with children living separately had lower levels of depression. Participation in clubs and political and social groups did not impact depression. Social activities explained 2.3% of depressive symptoms.
The total explanatory rate of the regression model was 31.4%. The perceived health status was the most powerful predictor of depression (β = −0.328, p < 0.001), followed by IADL (β = −0.161, p < 0.001), willingness to participate in social gatherings (β = −0.128, p < 0.001), frequency of visits and contact with children living separately (β = −0.095, p < 0.001), and income quintile (β = −0.095, p < 0.001).
The current study verified the relationships between demographic variables, health-related variables, physical function, social activities, and depression of older adults who live alone. Among the sociodemographic characteristics, gender, educational level, income quintile, and religion affected depression. Specifically, it is necessary to pay attention to the religious activities of older adults who live alone. Religious activities may contribute to preventing depressive symptoms as they can provide opportunities to supplement lack of social support (Sohn, 2008). Older men living alone had more depressive symptoms than older women living alone. These results suggest that older men may be more vulnerable to depression than older women.
Perceived health status was found to be negatively related to depression, whereas diabetes, stroke, angina and myocardial infarction, osteoarthritis, and rheumatoid arthritis were not found to affect depression in older adults living alone. These findings are in agreement with results of a meta-analysis of older adults with depression in which subjective health status was more related to depression in older adults than physical disease (Leibson et al., 1999; Wolinsky et al., 1988). These results suggest that the subjective perception of older adults' health condition relates more to depression than simply the presence or absence of physical disease.
Physical function was found to have a negative effect on depression, suggesting that maintaining physical function can help prevent depression. On the other hand, decreased physical function can have psychological effects in older adults who live alone, reducing their social activities and potentially resulting in depression. According to related studies, physical and social activities are known to be major variables in maintaining physical function (Soubelet, 2013). Therefore, efforts to encourage physical and social activities are needed.
The key result of the current study was to verify the relationship between social activity and depression of older adults who live alone. The study found that the frequency of visits and contact with children living separately and networking have a significant effect on the depressive symptoms of these older adults. These results are similar to those of previous studies that showed overall social activities reduce depression in older adults who live alone (Croezen et al., 2015; Holtfreter et al., 2017; Solomonov et al., 2019). On the other hand, it was found that participation in clubs and political and social groups was not related to depression. The relationship between participation in clubs and political activities and depression has not been clarified in previous studies.
The current study had limitations. First, because the study was conducted using a cross-sectional design, the causal relationship between predictors and depressive symptoms cannot be confirmed. Second, the study identified the relationship between the presence of specific social activities and depression. In future studies, it will be necessary to assess the effects of social activities on depression in older adults by using a subjective evaluation of the degree of social activity and objective indicators of social activity.
Implications for Clinical Practice
Older adults who live alone may lack social support or emotional stability compared to other populations. The current study suggests that contact with children and social activities can reduce emotional problems in older adults who live alone. Therefore, mental health providers, including mental health nurses, need to be more aware of the importance of social activities, so they can encourage participation in these activities for older adults who live alone.
The frequency of visits and contact with children living separately was found to have the greatest effect on depression in older adults who live alone. Children are an important source of emotional stability. Therefore, frequent visits and contact with children can reduce loneliness experienced by older adults who live alone, consequently reducing depression. Social gatherings can also contribute to reducing depression (Croezen et al., 2015). Senior citizen centers, which are part of Korean culture, are places where older adults can share information, promote friendship, and maintain social relationships, which can help prevent depressive symptoms.
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Participant Demographics (N = 2,258)
| Female||1,838 (81.4)|
| Male||420 (18.6)|
| No formal education (illiterate)||919 (40.7)|
| No formal education (literate)||714 (31.6)|
| Primary school||270 (11.9)|
| Middle school||247 (10.9)|
| High school or higher||109 (4.8)|
| Yes||1,485 (65.7)|
| No||774 (34.3)|
|Gross household incomea|
| First income quintile||578 (25.6)|
| Second income quintile||551 (24.4)|
| Third income quintile||573 (25.4)|
| Fourth income quintile||557 (24.7)|
|Mean (SD) (Range)|
|Age (years)||75.9 (6.8) (65 to 99)|
The results of Pearson correlation analysis between variables
Hierarchical regression analysis
|Independent variables||Final Model (Model 4)|
|Perceived health status||−1.614||−.328||−17.654***|
|Angina and myocardial infarction||.423||.025||1.434|
|Osteoarthritis or rheumatism arthritis||.186||.021||1.107|
|The frequency of contact with children||−.260||−.095||−5.120***|
|Participation in Club||.500||.020||1.137|
|Political and social group||.299||.004||.219|