INTRODUCTION

Depression has become increasingly prevalent among older adults, and its true burden is likely underestimated because depression is often underdiagnosed in this population [1]. Mental disorders such as depression are major causes of suicide among older adults, who have the highest suicide rate in most countries [2]. Identifying potentially modifiable factors associated with depression in older adults could therefore assist public health efforts in developing preventive strategies.

The number of the “oldest old”—those aged 80 years or older—is projected to reach 265 million globally by the mid-2030s [3]. However, this group often remains overlooked, even in studies addressing chronic conditions such as hypertension that require lifelong management [4]. Older adults are about 8 times more likely to live alone than younger or middle-aged adults, and the oldest old are at even greater risk of living alone [5]. Living alone contributes to increased loneliness among this group [6], which, in turn, leads to depressive symptoms [7].

As life expectancy increases, the likelihood of widowhood also rises, making it more common for older adults to live alone for extended periods [8]. In Asian societies, family-based care has traditionally been the preferred option for older adults. However, the rapid transition from extended to nuclear family structures has reduced the availability of such caregiving [9]. Without traditional family support, older adults living alone in Asia have shown a higher risk of depression [10,11].

Previous studies have demonstrated that older adults living alone face a higher risk of depression compared with those residing with family. However, the combined influence of residential status and family interaction requires further examination. It remains uncertain whether interaction with non-cohabiting family members provides the same psychological protection as traditional co-residence. In particular, the effect of family interaction from relatives not living together with older adults has not been adequately evaluated.

This study therefore addressed 2 objectives. First, it examined the underexplored relationship between residential status and family interaction frequency among older Korean adults aged ≥80 years. Second, it investigated whether sufficiently frequent family interaction can mitigate the impact of living alone on depressive symptoms in this population.

METHODS

Study Design

This cross-sectional study examined the role of family interaction frequency in depressive symptoms among older adults aged ≥80 years who lived alone, with analyses stratified by gender and disability status. Data were obtained from the 2019 Korea Community Health Survey (KCHS-19). The KCHS is an annual nationwide survey organized by the Korea Disease Control and Prevention Agency that collects nationally representative data from Korean adults aged ≥19 years.

Participants and Data Collection

Among the 229 099 participants of KCHS-19, a total of 16 022 participants aged ≥80 years were assessed for eligibility for this study. Of these, 6834 participants lived alone, and 9188 participants lived with close family such as children or a spouse (6111 lived with a spouse, 2304 with children, and 773 with both spouse and children). Participants living with other individuals, such as siblings or non-relatives, were considered ineligible. Those living with close family served as the reference group. Eligible participants with missing or non-response data for family interaction frequency, the Patient Health Questionnaire-9 (PHQ-9), the usual activities dimension of the EuroQol 5-Dimension (EQ-5D), or potential confounders were excluded from the analysis (n=464). The majority of missing responses were related to the PHQ-9 (n=206) and household income (n=323). In total, 15 672 participants were included in the final analysis. The response rate was 97.4% (Supplemental Material 1).

Participants were categorized based on their residential status and family interaction frequency. Those living with a spouse and/or children—co-residence patterns associated with a lower risk of depressive symptoms among older adults—were classified as living with close family [12,13]. Participants living alone were further categorized according to the frequency of interaction with family members or other relatives. Family interaction frequency was assessed using the question, “How often do you see or communicate with the most frequently contacted family member?” According to the KCHS-19 Survey Question Guidelines, “see or communicate” refers only to bidirectional, real-time communication, such as in-person meetings, phone calls, or video calls. It excludes asynchronous communication methods such as mail, email, messenger services, blogs, or social networking services (e.g., Facebook, Twitter). Family members residing together were not eligible to be counted as the “most frequently contacted family member.” If a respondent reported no contact with any family member, the response was categorized as “less than once a month” [14]. Family interaction frequencies were divided into 4 groups: less than once a month, 1–3 times a month, once a week, and more than once a week. The detailed distribution of participants is presented in the Supplemental Material 2.

The outcome variable was the presence of depressive symptoms as measured by the PHQ-9, a validated screening tool for major depressive disorder with high sensitivity and specificity [15]. The PHQ-9 consists of 9 questions, each scored from 0 to 3, yielding a total score range of 0–27. A PHQ-9 score ≥10, indicating moderate to severe depressive symptoms requiring antidepressant treatment, was used as the cutoff for defining depressive status [16,17].

Stratified analyses were performed by gender and self-reported difficulty in daily activities. The incidence of depression differs markedly by gender [18], and older adults who experience difficulty in daily activities may have an increased need for regular support from others. Therefore, we explored how gender and difficulty in daily activities influenced the association between living arrangement and depressive symptoms. Difficulty in daily activities was assessed using the usual activities dimension of the EuroQol 5-Dimension 3-Level (EQ-5D-3L) system, which comprises 5 dimensions (mobility, self-care, usual activities, pain/discomfort, and anxiety/depression), each rated on 3 levels: no problems, moderate problems, and extreme problems [19]. The “usual activities” dimension was used to indicate difficulty in daily activities. For the stratified analysis, “no problems in usual activities” was categorized as “without difficulty,” whereas “moderate or extreme problems” were categorized as “with difficulty.”

Age, economic activity, residential location, hypertension and diabetes diagnoses, and interactions with neighbors and friends were considered potential confounders. Age was divided into 3 groups of 5-year intervals (80–84, 85–89, and ≥90 years). Household income was categorized into 3 groups based on 2 million Korean won (KRW) intervals (approximately 1500 US dollar as of 2024): <2 million KRW/mo (low), <4 million KRW/mo (middle), and ≥4 million KRW/mo (high). Economic activity was classified as “yes” if participants were employed full-time or part-time. Residential location was categorized as urban or rural. Hypertension and diabetes were determined based on self-reported physician diagnoses. The number of chronic diseases diagnosed was derived from participants’ self-reported hypertension and diabetes status. Because poor social networks are associated with adverse health outcomes among older adults [20], interaction frequency with neighbors and friends was used to approximate participants’ social network strength. An interaction frequency of less than once a month was used as the cutoff.

Statistical Analysis

To compare differences in general characteristics between groups, the frequency and percentage of each variable were calculated. Percentages were derived using the weighted values provided in the KCHS-19. The chi-square test was used to assess significant differences in variables according to residential status. In addition, the prevalence of depressive symptoms over the survey period was plotted by residential status and family interaction frequency to provide an overview of depressive symptom patterns in the Korean community. Depressive symptoms measured by PHQ-9 were available for KCHS-17 through KCHS-24, and family interaction frequency was available for KCHS-17, KCHS-19, and KCHS-23. Variance inflation factors (VIFs) were calculated to test for potential multicollinearity among confounders. The VIFs of the potential confounders ranged from 1.02 to 1.20, indicating no multicollinearity [21]. Multivariate logistic regression analysis was conducted to evaluate the independent effects of family interaction frequency on the prevalence of depressive symptoms after adjusting for potential confounders, as well as to examine these associations by gender and difficulty in daily activities. To clarify the potential effects of interaction frequency with neighbors and friends, model 1 was adjusted for age group, household income, economic activity, residential location, and the number of diagnosed chronic diseases. Model 2 was further adjusted for interaction frequency with neighbors and interaction frequency with friends, in addition to the confounders included in model 1.

Several sensitivity analyses were performed to confirm the robustness of the study findings. First, participants living with other blood relatives, such as siblings, were merged with those living with close family and compared with participants living alone. Second, an additional analysis was conducted that included subjective cognitive impairment as a potential confounder, acknowledging possible inaccuracies due to the self-reported nature of the KCHS interviews. Participants who reported difficulty in daily activities caused by cognitive decline during the past year were categorized as having subjective cognitive impairment.

All analyses were performed using SAS version 9.4 (SAS Institute Inc., Cary, NC, USA). A complex sample design was applied to account for survey weighting. After applying the Bonferroni correction for multiple comparisons, the significance threshold was set at α<0.05/20=0.0025. The p-values for the primary analyses are presented in the Supplemental Material 3. The statistical significance of the primary analyses remained consistent regardless of whether the threshold was set at α=0.05 or α=0.0025.

Ethics Statement

According to Article 2 of the Enforcement Rule of the Bioethics and Safety Act, the KCHS has been exempt from Institutional Review Board (IRB) review by the Korea Centers for Disease Control and Prevention since 2017, as it is a government-commissioned project designed to assess and evaluate public welfare. This study was approved by the IRB of the Catholic University of Korea (IRB No. MC20ZESI0046).

RESULTS

Of the 15 672 participants, 9020 lived with close family, and 6652 lived alone. Approximately half of those living with close family were women (45.6%), whereas the majority of older adults living alone were women regardless of family interaction frequency (77.9–87.5%). A higher proportion of older adults living alone reported depressive symptoms (9.4–14.1%) compared with those living with close family (6.5%) (Table 1). Older adults living alone consistently showed a higher prevalence of depressive symptoms, and among them, those with a family interaction frequency of less than once a month exhibited the highest prevalence rate (Supplemental Material 2).

Compared with older adults living with close family, those living alone with a family interaction frequency of less than once a month had a significantly higher likelihood of reporting depressive symptoms (adjusted odds ratio [aOR], 1.71; 95% confidence interval [CI], 1.36 to 2.15). The association between living alone and depressive symptoms remained significant for participants with a family interaction frequency of 1–3 times a month (aOR, 1.51; 95% CI, 1.22 to 1.87). However, for those interacting with family once a week, the likelihood of reporting depressive symptoms was not significantly higher than that of older adults living with close family (aOR, 1.10; 95% CI, 0.84 to 1.42) (Table 2, Supplemental Material 4).

When stratified by gender, there was no significant increase in the odds of reporting depressive symptoms among men with a family interaction frequency of 1–3 times a month (aOR, 1.34; 95% CI, 0.74 to 2.40) or among women with a frequency of once a week (aOR, 1.06; 95% CI, 0.80 to 1.41) (Table 3).

Among participants with difficulty in daily activities, a family interaction frequency of once a week mitigated the impact of living alone on depressive symptoms (aOR, 1.10; 95% CI, 0.82 to 1.47) (Table 4).

The associations between family interaction frequency and depressive symptoms among participants living alone remained consistent in the sensitivity analyses, in which older adults living with any family members were used as the reference group (Supplemental Materials 5-7). The association also remained robust when subjective cognitive impairment was included as an adjustment variable (Supplemental Material 8).

DISCUSSION

Our study demonstrated that older adults aged ≥80 years who lived alone and had family interaction less than once a month were 71% more likely to report depressive symptoms compared to those living with close family members such as a spouse or children. In contrast, older adults who interacted with family once a week did not show an increased likelihood of reporting depressive symptoms compared with those living with close family. Moreover, the protective effect of weekly family interaction on depressive symptoms among older adults remained consistent across subpopulations. Neither gender nor difficulty in daily activities showed a significant interaction effect on the association between family interaction and depressive symptoms, and older adults who interacted with family once a week exhibited similar odds of depressive symptoms as those living with close family.

The living arrangements of older adults are shaped by personal preferences, cultural norms, individual needs, and the availability of resources [22,23]. Older adults may live alone for various reasons, including personal choice, geographic separation from family, bereavement, or childlessness [24]. Participants who lived alone and interacted with family less than once per month likely represent individuals in undesirable living circumstances. A previous study reported that a mismatch between one’s current and preferred living arrangements, such as living alone when the preferred arrangement was to live with children, was associated with a higher risk of loneliness [25]. This discrepancy between current and desired arrangements may help explain the increased prevalence of depressive symptoms in our findings.

Because older adults living alone are less likely to receive support from others, many may not obtain timely care when needed [26], leading to an elevated risk of depression. Prior research also showed that older adults forced to live alone due to the loss of close relationships may experience greater psychological distress, such as depression, which can contribute to increased mortality risk [27]. Conversely, older adults living alone who maintain family interaction at least once a week likely represent those who have preserved emotional support and thus do not suffer the same adverse consequences of isolation. A study of older Germans (mean age >80 years) found that emotional loneliness caused by the loss or absence of a close attachment figure was associated with increased mortality risk [28]. It is plausible that, among older adults living alone, children who maintain regular contact may continue to serve as key emotional attachment figures, providing psychological protection.

Our analysis also revealed that poor economic status, comorbid chronic diseases, and limited social connections with friends or neighbors were associated with higher odds of depressive symptoms. Public-sector support should therefore be prioritized for older adults lacking familial support and facing multiple risk factors for poor mental health.

A prior study involving socially isolated older adults with disabilities found that regular phone calls from laypersons did not significantly reduce moderate depressive symptoms [29]. Notably, our findings suggest that interaction with family members—rather than acquaintances—was associated with a significant reduction in moderate to severe depressive symptoms, which are linked to an increased risk of late-life suicidal ideation and behavior [30]. Another study on social relationships indicated that the quality of interaction, reflected in perceived social support, has a greater influence on depressive symptoms than the quantity of interaction [31]. Perceived social support refers to an individual’s belief that someone is available to provide help in times of need [32]. Older adults who maintain regular contact with their children may trust that their children will offer assistance when necessary, strengthening their sense of security and emotional well-being.

This study has several limitations. First, as this analysis was based on secondary data, only confounding variables available in the KCHS-19 dataset were used. Information on the specific family members involved in interactions, the mode of communication, the geographic distance between residences, and the quality of interactions was unavailable. However, a prior study of Korean older adults found that the most frequently contacted non-cohabiting family members were typically the eldest son or daughter, followed by younger children and the spouse of the eldest son, and that most did not live within walking distance [33]. Thus, most family interactions likely occurred through non-face-to-face means such as phone or video calls. Potential sources of emotional support from non-family members—such as community welfare workers or pets—were also not captured in the KCHS-19. Furthermore, the study sample comprised community-dwelling older adults capable of maintaining independent living, thus excluding more frail populations. Lastly, given the cross-sectional design, it is possible that preexisting depressive symptoms influenced residential status. Nonetheless, a recent systematic review demonstrated a causal relationship between living alone and depression [34]. Moreover, family members who already interact with older adults may increase contact frequency when these individuals develop physical or mental illness, potentially leading to an underestimation of the true protective effect of frequent family interaction on depressive symptoms.

Despite these limitations, the KCHS-19 provides nationwide coverage across all administrative districts of Korea and is administered by trained interviewers to minimize bias and measurement error. The participants in this study are representative of the Korean population. Importantly, this study differentiated older adults living alone into subgroups based on family interaction frequency and demonstrated that sufficiently frequent family interaction can mitigate the adverse effects of living alone on mental health. These findings also suggest that information and communication technologies may play a valuable role in facilitating family contact and supporting older adults’ mental well-being.

This study found that older adults living alone who interacted with family members once a week or more did not have increased odds of depressive symptoms compared with those living with close family. As life expectancy continues to rise and household composition changes, the proportion of older Koreans living alone will inevitably increase. Promoting regular family interaction may therefore represent an effective strategy to mitigate the heightened risk of depression associated with living alone.

Supplemental Materials

Notes

Conflict of Interest

The authors have no conflicts of interest associated with the material presented in this paper.

Funding

None.

Acknowledgements

None.

Author Contributions

Conceptualization: Hwang HA, Bae BY, Yim HW. Data curation: Yun M, Choi J. Formal analysis: Hwang HA, Jeong H, Yim HW. Funding acquisition: None. Methodology: Hwang HA, Jeong H, Yim HW. Project administration: Jeong H, Yim HW. Visualization: Choi J, Jeong Y. Writing – original draft: Hwang HA. Writing – review & editing: Bae BY, Jeong H, Yun M, Choi J, Jeong Y, Yim HW.

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Figure & Data

References

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