Introduction
The novel coronavirus disease (COVID-19) may have psychological impacts on the general population as well as healthcare workers (World Health Organization, 2020). In particular, many experts have raised concerns about older adults being a potential high-risk group for depression because they could be seriously affected by social isolation, bereavement, and limited access to online mental health services amidst this unprecedented pandemic (Holmes et al., Reference Holmes, O'Connor, Perry, Tracey, Wessely, Arseneault and Bullmore2020; Jawaid, Reference Jawaid2020; Yang et al., Reference Yang, Li, Zhang, Zhang, Cheung and Xiang2020).
The prevalence of depression in the general population has been found to vary widely from 5.9% to 52.5% during the COVID-19 pandemic (Ahmed et al., Reference Ahmed, Ahmed, Aibao, Hanbin, Siyu and Ahmad2020; Choi, Hui, & Wan, Reference Choi, Hui and Wan2020; Ettman et al., Reference Ettman, Abdalla, Cohen, Sampson, Vivier and Galea2020; Gao et al., Reference Gao, Zheng, Jia, Chen, Mao, Chen and Dai2020; Gonzalez-Sanguino, Ausin, Castellanos, Saiz, & Munoz, Reference Gonzalez-Sanguino, Ausin, Castellanos, Saiz and Munoz2020a; Hyland et al., Reference Hyland, Shevlin, McBride, Murphy, Karatzias, Bentall and Vallieres2020; Lei et al., Reference Lei, Huang, Zhang, Yang, Yang and Xu2020; Mazza et al., Reference Mazza, Ricci, Biondi, Colasanti, Ferracuti, Napoli and Roma2020; Ozdin & Bayrak Ozdin, Reference Ozdin and Bayrak Ozdin2020; Palgi et al., Reference Palgi, Shrira, Ring, Bodner, Avidor, Bergman and Hoffman2020; Shi et al., Reference Shi, Lu, Que, Huang, Liu, Ran and Lu2020; Sonderskov, Dinesen, Santini, & Ostergaard, Reference Sonderskov, Dinesen, Santini and Ostergaard2020; Tan et al., Reference Tan, Hao, McIntyre, Jiang, Jiang, Zhang and Tam2020; Wang et al., Reference Wang, Pan, Wan, Tan, Xu, Ho and Ho2020a). Research results are also conflicting with respect to changes in depressive symptoms, with one study finding an increase in depressive symptoms (Gonzalez-Sanguino et al., Reference Gonzalez-Sanguino, Ausin, Castellanos, Saiz, Lopez-Gomez, Ugidos and Munoz2020b), another finding no change (Wang et al., Reference Wang, Pan, Wan, Tan, Xu, McIntyre and Ho2020b), and yet another study finding a decrease in symptoms (Fancourt, Steptoe, & Bu, Reference Fancourt, Steptoe and Bu2021). There are several prospective studies that have compared the severity of depressive symptoms before and during the pandemic (Ettman et al., Reference Ettman, Abdalla, Cohen, Sampson, Vivier and Galea2020; Pan et al., Reference Pan, Kok, Eikelenboom, Horsfall, Jorg, Luteijn and Penninx2020; Racine et al., Reference Racine, Hetherington, McArthur, McDonald, Edwards, Tough and Madigan2021; Thorisdottir et al., Reference Thorisdottir, Asgeirsdottir, Kristjansson, Valdimarsdottir, Jonsdottir Tolgyes, Sigfusson and Halldorsdottir2021). However, none of the previous studies investigated the effect of the COVID-19 pandemic on the risk of depressive disorders. All of the previous studies examined depressive symptoms using self-reported questionnaires through web- or app-based online surveys, which are subject to substantial selection biases, particularly with respect to older adults who are less likely to be proficient with digital devices (Pierce et al., Reference Pierce, McManus, Jessop, John, Hotopf, Ford and Abel2020b). Most of the previous studies either excluded older individuals from their samples (Ahmed et al., Reference Ahmed, Ahmed, Aibao, Hanbin, Siyu and Ahmad2020; Ettman et al., Reference Ettman, Abdalla, Cohen, Sampson, Vivier and Galea2020; Gao et al., Reference Gao, Zheng, Jia, Chen, Mao, Chen and Dai2020; Gonzalez-Sanguino et al., Reference Gonzalez-Sanguino, Ausin, Castellanos, Saiz and Munoz2020a; Lei et al., Reference Lei, Huang, Zhang, Yang, Yang and Xu2020; Mazza et al., Reference Mazza, Ricci, Biondi, Colasanti, Ferracuti, Napoli and Roma2020; Ozdin & Bayrak Ozdin, Reference Ozdin and Bayrak Ozdin2020; Racine et al., Reference Racine, Hetherington, McArthur, McDonald, Edwards, Tough and Madigan2021; Shi et al., Reference Shi, Lu, Que, Huang, Liu, Ran and Lu2020; Tan et al., Reference Tan, Hao, McIntyre, Jiang, Jiang, Zhang and Tam2020; Thorisdottir et al., Reference Thorisdottir, Asgeirsdottir, Kristjansson, Valdimarsdottir, Jonsdottir Tolgyes, Sigfusson and Halldorsdottir2021; Wang et al., Reference Wang, Pan, Wan, Tan, Xu, Ho and Ho2020a, Reference Wang, Pan, Wan, Tan, Xu, McIntyre and Ho2020b) or did not separately analyze the effect of the COVID-19 pandemic in older adults (Choi et al., Reference Choi, Hui and Wan2020; Fancourt et al., Reference Fancourt, Steptoe and Bu2021; Gonzalez-Sanguino et al., Reference Gonzalez-Sanguino, Ausin, Castellanos, Saiz, Lopez-Gomez, Ugidos and Munoz2020b; Hyland et al., Reference Hyland, Shevlin, McBride, Murphy, Karatzias, Bentall and Vallieres2020; Palgi et al., Reference Palgi, Shrira, Ring, Bodner, Avidor, Bergman and Hoffman2020; Pan et al., Reference Pan, Kok, Eikelenboom, Horsfall, Jorg, Luteijn and Penninx2020; Sonderskov et al., Reference Sonderskov, Dinesen, Santini and Ostergaard2020). Although the factors associated with the risk of depressive disorders during the COVID-19 pandemic may be different from those before the pandemic, none of the previous studies investigated the differences in the risk factors for depressive disorders before and during the pandemic.
In the current study, we investigated the impact of the COVID-19 pandemic on the risk of depressive disorder by conducting face-to-face diagnostic interviews with the participants of the Korean Longitudinal Study on Cognitive Aging and Dementia (KLOSCAD) (Han et al., Reference Han, Kim, Kwak, Kim, Kim, Kim and Kim2018). We compared the incidence of and the risk factors for depressive disorder among the participants who responded to the follow-up assessment before and during the COVID-19 pandemic in South Korea (hereafter, Korea). In Korea, a complete lockdown policy was not introduced because the increase in the number of COVID-19 cases was not considerable.
Methods
Study design, setting, and participants
KLOSCAD is a nationwide, population-based, prospective cohort study of elderly Koreans (Han et al., Reference Han, Kim, Kwak, Kim, Kim, Kim and Kim2018). For KLOSCAD, 6818 community-dwelling Koreans aged 60 years or above were randomly sampled from 30 villages and towns of 13 districts across Korea using the national residential rosters of 2010. The baseline assessment was conducted from November 2010 to October 2012, and follow-up assessments have been conducted every 2 years; the first follow-up assessment was carried out from November 2012 to October 2014, the second from November 2014 to October 2016, the third from November 2016 to October 2018, and the fourth from January 2019 to November 2020. At the baseline assessment, a half of the participants were evaluated in the first year and the rest in the second year. The order of evaluation at the baseline assessment was randomly assigned. The participants who were evaluated in the first year of the baseline assessment have been evaluated in the first year of every follow-up duration of the participants. The numbers of participants who completed the baseline assessment and the four follow-up assessments were 6818, 5131 (75.3%), 4181 (61.3%), 3426 (50.2%), and 2518 (36.9%), respectively.
From among the 2518 participants who completed the fourth follow-up assessment, we included 2308 participants in the current analysis after excluding those who did not respond to the assessment of depressive disorders (N = 146), did not respond to the third follow-up assessment (N = 25), or completed the fourth follow-up assessment between December 2019 and January 2020 (N = 39). We excluded the 39 participants who completed the fourth follow-up assessment between December 2019 and January 2020 from the current analysis because the psychological impact of COVID-19 on the general population just around the time of the outbreak might be unclear. Among the 2308 participants included in our analysis, 1348 (58.4%) completed their fourth follow-up assessment before the COVID-19 outbreak (pre-pandemic group; followed from 1 January 2019 to 30 November 2019) and 960 (41.6%) completed it after the COVID-19 outbreak (intra-pandemic group; followed from 1 February 2020 to 30 November 2020). At the time of assessment, none of the participants had been diagnosed with COVID-19 or had any symptoms of the disease such as fever, cough, sore throat, dyspnea, myalgia, fatigue, and loss of taste or smell. The demographic and clinical characteristics of the participants are summarized in Table 1. In addition, online Supplementary Table S1 summarizes our comparison of the demographic and clinical characteristics of the participants of the third follow-up assessment who responded to the fourth follow-up and those who did not respond to the fourth follow-up assessment or were excluded from the current analysis.
Table 1. Demographic and clinical characteristics of the participants
F/U, follow-up assessment; CIRS, Cumulative Illness Rating Scale; GDS, Geriatric Depression Scale.
a Participants who completed their 4th follow-up assessment before the COVID-19 outbreak.
b Participants who completed their 4th follow-up assessment after the COVID-19 outbreak.
c Covered by the National Medicaid Program.
d Less than 1 h per week.
e Under 600 metabolic equivalent task minutes per week.
f Drinking above 7 standard units per week within the past one year.
* p Values for group, time, and time×group interaction from generalized estimating equations; bold values for p < 0.05 in time × group interaction.
All participants were fully informed about the study protocol and they provided written informed consent. This study was approved by the Institutional Review Board of the Seoul National University Bundang Hospital.
Assessment of depressive disorder and depressive symptoms
Geriatric psychiatrists performed a face-to-face standardized diagnostic interview with each participant using the Korean version of the Mini International Neuropsychiatric Interview (MINI-K) (Sheehan et al., Reference Sheehan, Lecrubier, Sheehan, Amorim, Janavs, Weiller and Dunbar1998). The diagnostic interview using the MINI-K was administered after the evaluations by trained research nurses and neuropsychological researchers with an interval of 1 week. We made a diagnosis of depressive disorder when a participant exhibited major or minor depressive disorders according to the Diagnostic and Statistical Manual of Mental Disorders, 4th edition (DSM-IV) criteria or subsyndromal depression according to the operational diagnostic criteria (Oh et al., Reference Oh, Han, Kim, Kwak, Kim, Kim and Kim2020). The participants without any current depressive disorder and manic/hypomanic episode were defined as euthymic participants. We used the Geriatric Depression Scale (GDS) to assess the severity of depressive symptoms (Kim et al., Reference Kim, Park, Lee, Huh, Lee, Han and Woo2008).
Assessment of potential risk factors
Trained research nurses evaluated sociodemographic and clinical factors such as age, sex, residential area, economic status, burden of comorbidities, cohabitants, social activities, physical activities, alcohol drinking, smoking, and use of anti-depressants. Persons supported by the National Medicaid Program were categorized as economically disadvantaged, those with a Cumulative Illness Rating Scale (CIRS) score of 5 points or higher were considered to have a high burden of comorbidities (Miller et al., Reference Miller, Paradis, Houck, Mazumdar, Stack, Rifai and Reynolds1992), and those with an exercise routine translating to less than 600 metabolic equivalent task minutes per week were considered to have a low level of physical activity (Ainsworth et al., Reference Ainsworth, Haskell, Whitt, Irwin, Swartz, Strath and Leon2000).
We also measured the frequency of family gatherings, religious activities, and social activities, and considered the level of each activity to be low when its frequency was less than 1 h per week.
Incident depressive disorders in participants diagnosed with dementia were not ascertained as incident cases. To diagnose dementia, geriatric psychiatrists administered standardized diagnostic interviews and physical examinations using the Korean version of the Consortium to Establish a Registry for Alzheimer's Disease Assessment Packet (CERAD-K) clinical assessment battery (Lee et al., Reference Lee, Lee, Lee, Kim, Jhoo, Kim and Woo2002) for all participants. Neuropsychological researchers administered a comprehensive neuropsychological battery that included CERAD-K (Lee et al., Reference Lee, Lee, Lee, Kim, Jhoo, Kim and Woo2004). Trained nurses administered laboratory tests including complete blood cell count, chemistry panels, serologic test for syphilis screening, thyroid function test, serum levels of vitamin B, and apolipoprotein E genotyping. A panel of geriatric psychiatrists confirmed the diagnosis of dementia based on the DSM-IV criteria.
Statistical analysis
We compared the changes in the demographic and clinical characteristics of the participants during the follow-up period using generalized estimating equation for each variable.
We examined the effect of the COVID-19 pandemic on changes in GDS scores during the follow-up period using generalized estimating equation after adjusting for age, sex, economic status, comorbidities, cohabitants, family gatherings, religious activities, social activities, physical activities, alcohol drinking, smoking, depressive disorders, and the follow-up interval. We examined the correlates of the changes in GDS scores during the follow-up period in the pre-pandemic and intra-pandemic groups separately using generalized estimating equations after adjusting for follow-up duration.
To investigate the effect of the COVID-19 pandemic on the future risk of depressive disorder, we separately analyzed the 1963 participants who were euthymic and not using any anti-depressant at the third follow-up assessment. We estimated the age- and sex-adjusted 2-year incidence of depressive disorder by direct standardization based on the 2010 National Census data. We examined the effect of the COVID-19 pandemic on the risk of incident depressive disorder during the follow-up period using multivariate logistic regression analyses after adjusting for a history of depressive disorders, age, sex, economic status, comorbidities, cohabitants, family gatherings, religious activities, social activities, physical activities, alcohol drinking, smoking, and follow-up interval. We examined the factors associated with the risk of incident depressive disorder in the pre-pandemic and intra-pandemic groups separately using multivariate logistic regression analyses.
As sensitivity analyses, we examined the effects of dementia on the changes in the GDS scores and on the risk of incident depressive disorder in the intra-pandemic group using generalized estimating equations and multivariate logistic regression analyses respectively with adjustments of same covariates as above.
We performed all statistical analyses using IBM SPSS Statistics, version 19.0 (IBM Corporation).
Results
As summarized in Table 1, 2308 participants completed both the third and the fourth follow-up assessments. Among them, 1348 completed the fourth follow-up assessment before the COVID-19 pandemic and 960 after the outbreak. The follow-up interval of the intra-pandemic group was longer than that of the pre-pandemic group (27.7 ± 2.7 v. 24.6 ± 2.0 months, p < 0.001). The intra-pandemic group was older and had lower proportion of participants with a low level of physical activity than the pre-pandemic group. Although the CIRS scores were comparable between the two groups, they increased during the follow-up period, with the increase in the intra-pandemic group lower than that in the pre-pandemic group. The number of drinkers and smokers was comparable between the two groups and decreased during the follow-up period in both groups. The intra-pandemic group had fewer participants with a low frequency of family gatherings and social activities but more participants with a low level of religious activities than the pre-pandemic group. During the follow-up period, the number of participants with a low frequency of family gatherings remained stable, while the number of those with a low frequency of religious and social activities increased, with this increase larger in the intra-pandemic group than the pre-pandemic group (Table 1). The number of participants with dementia was comparable between two groups (p = 0.071) and increased during the follow-up period in both groups (from 3.8% to 5.1% in pre-pandemic group; from 2.5% to 3.6% in intra-pandemic group, p value for time × group interaction = 0.642).
Although the intra-pandemic group and the pre-pandemic group had comparable GDS scores and rates of depressive disorders, the intra-pandemic group had fewer anti-depressant users than the pre-pandemic group. During the follow-up period, the increase in the incidence of depressive disorder was comparable between the two groups. However, the intra-pandemic group showed a greater increase in the GDS score than the pre-pandemic group (Table 1). Multivariate generalized estimated equation analysis revealed that the COVID-19 pandemic was significantly associated with the increase in the GDS score during the follow-up period [from 8.6 ± 6.3 points to 9.0 ± 6.4 points; b (standard error, s.e.) = 0.42 (0.20), p = 0.040].
The correlates of the increase in GDS scores during the follow-up period mostly overlapped between the two groups (older age, women, economic disadvantage, high CIRS score, low frequency of religious activities, low frequency of social activities, current smoking, and depressive disorders). However, a low level of physical activity was associated with an increase in GDS scores in the pre-pandemic group only while a low frequency of family gatherings was linked to an increase in GDS scores in the intra-pandemic group only (Table 2). The follow-up duration was significantly associated with the changes in GDS scores in intra-pandemic group [b (s.e.) = −0.20 (0.07), p = 0.002]. The presence of dementia did not affect the changes in GDS score during the pandemic [b (s.e.) = 1.58 (1.15), p = 0.167].
Table 2. The estimated effects of the correlates on the depressive symptoms by the influence of COVID-19 pandemica
b, β coefficient; s.e., standard error.
a Multivariate generalized estimated equation adjusted for the follow-up duration.
b Participants who completed their fourth follow-up assessment before the COVID-19 outbreak.
c Participants who completed their fourth follow-up assessment after the COVID-19 outbreak.
d Covered by the National Medicaid Program.
e Cumulative Illness Rating Scale total scores of 5 points or higher.
f Less than 1 h per week.
g Under 600 metabolic equivalent task minutes per week.
h Drinking above 7 standard units per week within the past 1 year.
Then, we analyzed 1963 participants separately (1121 in the pre-pandemic group and 842 in the intra-pandemic group) who were euthymic and not using anti-depressants at the time of the third follow-up assessment (Table 3). During the follow-up period, 104 participants (53 from the pre-pandemic group and 51 from the intra-pandemic group) developed depressive disorder. The age- and sex-adjusted 2-year incidence of depressive disorder was 4.6% [95% confidence interval (CI) 3.3–5.8] in the pre-pandemic group and 5.2% (95% CI 3.7–6.7) in the intra-pandemic group. Multivariate logistic regression analysis revealed that the COVID-19 pandemic doubled the risk of incident depressive disorder [odds ratio (OR) 2.00, 95% CI 1.18–3.38, p = 0.010]. This was also the case when we separately analyzed euthymic participants without a previous history of mood disorder (OR 2.44, 95% CI 1.18–5.02, p = 0.016).
Table 3. Characteristics of the participants who were euthymic at the third follow-up assessment
F/U, follow-up assessment; CIRS, Cumulative Illness Rating Scale.
a Participants who completed their 4th follow-up assessment before the COVID-19 outbreak.
b Participants who completed their 4th follow-up assessment after the COVID-19 outbreak.
c Covered by the National Medicaid Program.
d Less than 1 h per week.
e Under 600 metabolic equivalent task minutes per week.
f Drinking above 7 standard units per week within the past one year.
* p Values for group, time, and time×group interaction from generalized estimating equations.
A previous history of depression was associated with the risk of incident depressive disorder in both the pre-pandemic and intra-pandemic groups. A low frequency of family gatherings was associated with the doubled risk of incident depressive disorder in the intra-pandemic group only, while fewer social activities were associated with the doubled risk of incident depressive disorder in the pre-pandemic group only (Table 4). The follow-up duration was not associated with the risk of incident depressive disorder in intra-pandemic group (OR 0.99, 95% CI 0.87–1.12, p = 0.811). The presence of dementia was not associated with the risk of incident depressive disorder during the pandemic (OR 0.28, 95% CI 0.03–2.65, p = 0.264).
Table 4. Risk factors of incident depressive disorders in the pre-pandemic and intra-pandemic groupsa
OR, odds ratio; CI, confidence interval.
a Odds ratios from multivariate logistic regression analyses adjusted for the follow-up duration were presented; bold values for p < 0.05.
b Participants who completed their fourth follow-up assessment before the COVID-19 outbreak.
c Participants who completed their fourth follow-up assessment after the COVID-19 outbreak.
d Covered by the National Medicaid Program.
e Cumulative Illness Rating Scale total scores of 5 points or higher.
f Less than 1 h per week.
g Under 600 metabolic equivalent task minutes per week.
h Drinking above 7 standard units per week within the past 1 year.
Discussion
This study found that the COVID-19 pandemic was significantly associated with the risk of depressive disorder as well as depressive symptoms in older adults, with older adults who had a low frequency of family gatherings being at a higher risk of depression during the COVID-19 pandemic.
The UK Household Longitudinal Study found that the increase in general mental distress during the COVID-19 pandemic was more subtle in older adults than in younger adults. In that study, the average change in the 12-item General Health Questionnaire after the pandemic outbreak was just 0.8 points in adults aged 55 years or older but 2.7 points in those aged below 24 years (Pierce et al., Reference Pierce, Hope, Ford, Hatch, Hotopf, John and Abel2020a). The recent longitudinal study from Denmark also found that the negative impact of the pandemic on the psychological well-being decreased by increasing ages (Vistisen, Sonderskov, Dinesen, & Ostergaard, Reference Vistisen, Sonderskov, Dinesen and Ostergaard2021). Several cross-sectional studies have also found that the prevalence of mental distress, depressive symptoms, anxiety, post-traumatic symptoms, and negative affect was lower in older adults than younger adults during the pandemic (Gonzalez-Sanguino et al., Reference Gonzalez-Sanguino, Ausin, Castellanos, Saiz and Munoz2020a; Klaiber, Wen, DeLongis, & Sin, Reference Klaiber, Wen, DeLongis and Sin2021; van Tilburg, Steinmetz, Stolte, van der Roest, & de Vries, Reference van Tilburg, Steinmetz, Stolte, van der Roest and de Vries2020). This may be explained by the relatively high psychological resilience of older adults during this unprecedented pandemic, which is contrary to the expectations of experts (Holmes et al., Reference Holmes, O'Connor, Perry, Tracey, Wessely, Arseneault and Bullmore2020).
In line with previous studies, the current study found that the increase in depressive symptoms in older adults who were in the middle of the pandemic was modestly higher than that in older adults who were not influenced by the pandemic. However, the incidence of depressive disorder was doubled in older adults who were in the middle of the pandemic compared to those who were not influenced by the pandemic after adjusting for various potential risk factors for depressive disorders. The changes in depressive symptoms decreased by the increasing follow-up duration, but the risk of incident depressive disorder was not affected by the follow-up duration during the pandemic. The impact of the COVID-19 pandemic on the risk of depression in older adults has not been well represented in previous studies that tracked the mean changes in depressive symptoms only using dimensional scales, but this risk should not be underestimated.
The effect of the COVID-19 pandemic on the risk of depressive disorder may be larger in areas where the pandemic situation is more serious compared to Korea. The spread of COVID-19 is relatively modest in Korea compared to most other countries. There were 166.9 cumulative confirmed cases and 3.01 cumulative deaths per 100 000 people in Korea as of 18 February 2021, far below the numbers in American (an average of 2198.0 cases and 38.58 deaths per 100 000) and European countries (an average of 4603.1 cases and 85.64 deaths per 100 000) (World Health Organization, 2021). Furthermore, depressive disorder, even when mild, can result in serious health-related outcomes including various morbidities and mortality in older adults (Blazer, Reference Blazer2003; Meeks, Vahia, Lavretsky, Kulkarni, & Jeste, Reference Meeks, Vahia, Lavretsky, Kulkarni and Jeste2011). Therefore, the impact of depressive disorder on the life of older adults may be even more serious in areas with a chronic shortage of medical resources for managing mental and physical illnesses. There have been concerns that people with mental illnesses would suffer from low accessibility to medical resources amidst the pandemic; recent data from the Chinese general population with mental illnesses showed that 22.0% of them could not maintain their routine psychiatric care visits and 35.3% of them self-reduced or stopped their medications (Zhou, Liu, Xue, Yang, & Tang, Reference Zhou, Liu, Xue, Yang and Tang2020). Online mental health services have been broadly adopted in China to overcome this problem of low accessibility, but only a few older adults with mental illness could benefit from such services due to the age-related ‘digital divide’ (Ju et al., Reference Ju, Zhang, Wang, Li, Ng and Li2020). A recent clinical trial examined the usefulness of a 4-week telephone program in improving depression and anxiety in homebound middle-aged and older adults (Kahlon et al., Reference Kahlon, Aksan, Aubrey, Clark, Cowley-Morillo, Jacobs and Tomlinson2021). In the same way, future studies should investigate the effectiveness of providing interventions for late-life depression through electronic tools such as mental health support hotlines or regular contact via telephone, as older adults are more familiar and comfortable with these tools than they are with the Internet or smartphone applications.
In the current study, a low frequency of family gatherings was found to be associated with the risk of incident depressive disorder and depressive symptoms in older adults during the COVID-19 pandemic but not before the pandemic. Meanwhile, a low level of engagement in social activities with peers was associated with the risk of incident depressive disorder only before the pandemic. This was similar to the pattern in younger adults. In a recent cross-sectional study from the USA, support from families protected younger adults against depressive symptoms during the COVID-19 pandemic but that from familiar others did not (Liu, Zhang, Wong, Hyun, & Hahm, Reference Liu, Zhang, Wong, Hyun and Hahm2020). Family gatherings and social activities with peers are the critical components of social connectedness in older adults (Van Orden et al., Reference Van Orden, Bower, Lutz, Silva, Gallegos, Podgorski and Conwell2020), and the loss of social connectedness exacerbated perceived social isolation and strongly predicted an increase in depressive symptoms in older adults (Santini et al., Reference Santini, Jose, York Cornwell, Koyanagi, Nielsen, Hinrichsen and Koushede2020). However, the impact of the COVID-19 pandemic on family gatherings and social activities has been different; the frequency of family gatherings has remained unchanged while social activities have largely decreased. This differential impact of COVID-19 may be attributable to the national social distancing policy, which has limited social activities more than family gatherings. Compared to other social relationships, familial relationships have a qualitatively different structure based on high homophily and homogeneity, and an intense affective bond (McPherson, Smith-Lovin, & Cook, Reference McPherson, Smith-Lovin and Cook2001). Therefore, familial connections may serve as the last bastion in buffering the impact of crises like the COVID-19 pandemic on the risk of depression. Since non-face-to-face social interactions have been proposed as an effective tool to manage social isolation in older adults (Van Orden et al., Reference Van Orden, Bower, Lutz, Silva, Gallegos, Podgorski and Conwell2020), it is worth investigating whether safe gatherings that follow social distancing norms can reduce the risk of depression in older adults with a low level of family support during the pandemic.
We found significant associations between a history of depression and the risk of incident depressive disorder in euthymic older adults, and those associations were similar before and during the COVID-19 pandemic. Although the pandemic did not pose an additional risk on older adults with a history of depression, they still should be the target population of prevention strategies for mental health promotion in the era of pandemics because they have a 5.6-fold higher association with the risk of incident depression than those without a history of depression. In countries under a lockdown in particular, the management of this at-risk group is essential because low accessibility to mental health services may aggravate that risk substantially.
Due to Korea's unique situation that is characterized by the absence of a complete lockdown policy and the steadily but moderately increasing numbers of people with COVID-19, the comprehensive face-to-face diagnostic assessments were relatively less affected by selection bias, which is common in online self-reported questionnaires. However, we must acknowledge that this study has some limitations. First, we did not administer the diagnostic tests for COVID-19 to the participants. However, we evaluated the history of COVID-19 infection of the participants and their family members who were living together. None of the participants or their family members had a history COVID-19 infection. Second, there might be a selective attrition bias, which could limit the generalizability of this study. Third, the psychological impact of the pandemic and the risk factors of depression during the pandemic might have been underestimated in the current study because the outbreak was relatively modest in Korea and accessibility to medical resources has been maintained well during the pandemic. Fourth, there might be a detection bias that interviewers might be more sensitive to detect depressive disorders in intra-pandemic group than in pre-pandemic group, although the risk of bias might be minimized by using structured diagnostic interview. Finally, all participants were living in the community. In older adults living in institutions, the impact of the COVID-19 pandemic may be different.
Conclusion
This study is significant because it is the first to demonstrate that the COVID-19 pandemic is associated with a doubling of the risk for depressive disorder in older adults and to suggest that the risk of depressive disorder may be mitigated by promoting family gatherings during the COVID-19 pandemic. It highlights the need to implement measures for maintaining or promoting family interactions and to evaluate whether contactless family gatherings are as effective in reducing the risk of depression in older adults as conventional family gatherings.
Supplementary material
The supplementary material for this article can be found at https://doi.org/10.1017/S0033291721005018.
Acknowledgements
None.
Financial support
This research was supported by a grant from the Korean Health Technology R&D Project, Ministry of Health, Welfare, Republic of Korea (grant no. A092077) and a grant from the Research of Korea Centers for Disease Control and Prevention (grant no. 2019-ER6201-01). The sponsors were not involved in the design and administration of the study; collection, management, analysis, or interpretation of the data; preparation, review, or approval of the manuscript; or decision to submit the manuscript for publication.
Conflict of interest
None.
