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. Author manuscript; available in PMC: 2023 May 1.
Published in final edited form as: J Appl Gerontol. 2022 Dec 23;42(5):962–971. doi: 10.1177/07334648221146770

The Risk for Loneliness and Major Depression among Solo Agers

Kathryn Betts Adams 1,5, Rupal Parekh 2, Rebecca L Mauldin 3, Richard H Fortinsky 4, David C Steffens 5
PMCID: PMC10081956  NIHMSID: NIHMS1855829  PMID: 36564863

Abstract

Solo agers may be vulnerable to social isolation and mental health sequelae, particularly if they lack close family or friendship ties. This study examined associations among indicators of solo aging, frequency of loneliness, and Major Depressive Disorder (MDD) among adults aged 60+. Depressed participants were diagnosed by a geriatric psychiatrist and control participants were not depressed. We hypothesized that older adults with more indicators of solo aging (i.e.., living alone, being unmarried, not having family or friends nearby) would be more often lonely and more likely to be depressed. In multivariate analyses controlling for health comorbidities and financial difficulty, each additional solo aging indicator significantly increased the likelihood of frequent loneliness, 95% CI OR [1.50, 2.80], and having a depression diagnosis 95% CI OR [1.04, 2.07]. Solo agers may be vulnerable to loneliness and depression, reinforcing the need for assessment and intervention for social isolation among older adults.

Keywords: Loneliness, Living alone, Major Depressive Disorder, Solo Aging

Introduction and Literature Review

Solo Aging

Life expectancies have risen dramatically throughout the last century in the United States and other developed nations. Along with this “demographic imperative” of aging, social and cultural factors have led to greater numbers of older adults living alone, many without close family support. “Elder orphans” is a term that has been applied to those who live alone and lack family or other close relationships to offer care or support (Carney, et al., 2016). In their review of the phenomenon, Carney and colleagues define “elder orphans” as older adults who are socially or physically isolated, are unmarried or unpartnered (whether widowed, divorced, or never married), and have no children or close family members available to serve as caregivers (Carney et al, 2016; Ianzito,2017). Using 2010 data from the Health and Retirement Study (HRS), these authors determined the prevalence of those at high risk for becoming elder orphans – unmarried and childless, or unmarried, with children who are not in contact – to be 22.6% of the study population. Those with no living or available siblings in addition comprised a smaller group.

Other authors have also examined this contemporary phenomenon, but have suggested the need for alternative terminology to “elder orphan” (Farrell, T. W., Catlin, C., Chodos, A. H., Naik, A. D., Widera, E., & Moye, J., 2019). Margolis and Verdery used data from the Health and Retirement Study to examine a similar concept that they termed “kinlessness” (2017). These authors examined the prevalence with national data from 1998-2010. They found that approximately 5.5% of adults over age 55 lacked both a spouse/partner or children, while 1.1% lacked any relatives.

Still others authors have studied the phenomenon, but called these older adults “solo agers” (Camp & Peterson, 2019; Marak, 2017), a phrase that may sound less pejorative to describe those aging alone. For the purpose of this paper, we refer to older adults who are unmarried and/or living alone as solo agers, while acknowledging that living alone without immediate social or family support and networks may increase the vulnerability of this group and lead them to become vulnerable solo agers. Concerns about vulnerable solo agers include lack of available caregivers when needed. Health and social service providers, in particular, become aware of older adults who lack obvious informal care partners when their needs exceed their capacity to manage independently.

Increased work participation and earnings among women, lower birth rates, higher divorce rates among middle-aged and older adults, and migration of young adults away from the geographic areas of their families of origin are among factors contributing to an increased proportion of older people aging alone without close family support. The size of the Baby Boomer population, compared to prior generations, is a factor in the increase of the solo ager population (Ortman, Velkoff & Hoga, 2014). Over one-third of Baby Boomers have no children, and this population is particularly vulnerable to aging alone with little to no social support (Carney et al., 2016; Lin & Brown, 2012). Meanwhile, the number of divorced and separated older adults in the United States has risen from 5.3% in 1980 to 15% in 2017 (Administration for Community Living, 2018).

To date, despite the increasing attention to solo aging among gerontological scholars and practitioners, there is a lack of research examining this growing population in relation to their susceptibility to loneliness and depression.

Social Connectedness, Social Isolation, Solo Aging, and Loneliness

Theories of Successful Aging, from Rowe and Kahn (1997) to more current theories, suggest that social connectedness remains crucial in later life (O’Rourke & Sidani, 2017) while social isolation presents risks to physical and mental health (Blazer, 2020; Choi, Irwin & Cho, 2015; Shankar, McMunn, Banks & Steptoe, 2011; Taylor, Taylor, Nguyen, Chatters, 2018). Gerontological research has established the positive effects of diverse elements of social connectedness, such as having a sense of belonging (Portacolone, Johnson, Halpern & Kotwin, 2020) and the availability of a personal confidant (Bookwala, Marshall & Manning, 2014). A review of studies on the effects of activity on wellbeing provides evidence for the primary importance of informal social activity, e.g. visiting and conversation, to wellbeing in later life (Adams, Leibbrandt & Moon, 2011; Victor, Scambler, Bond & Bowling, 2000).

Social isolation is defined as a lack of social connectedness. While it is tempting to equate social isolation with the concept of solo aging, the latter is specifically used to identify older adults who are aging without a partner or close family members. The solo ager may not be socially isolated, but may be at risk for becoming socially isolated as age-related health and functioning declines occur and the individual has few very close people to rely upon or to assist them in keeping up with social connections.

Early loneliness research posited two types of loneliness: Social and emotional (Weiss, 1984). Social loneliness relates to a perceived lack of desired social activity, social contacts or connections, and emotional loneliness relates to the perceived lack of a desired confidant, significant other, or intimate friend. Previous research has found lack of nearby friends to be associated with loneliness, particularly for those who lived alone (Eshbaugh, 2009). Solo agers—older adults who live alone, are unmarried, and lack close family—may be especially vulnerable to social loneliness as advanced age brings reduced functional capabilities (Ianzito, 2017; Schlecht, 2018) and independent social participation becomes more difficult. In addition, solo agers, who are by definition unmarried and either childless or distant from any children or other family members, may be vulnerable to emotional loneliness due to the lack an intimate partner or confidant. Solo aging places older adults at risk for both types of loneliness. And those solo agers with functional limitations are more likely to experience fractured social networks and loneliness due to their own withdrawal from family and friends for fear of being burdensome (Pinquart, 2003; Cohen-Mansfield, Hazan, Lerman & Shalom, 2015).

Solo Aging and Depression

The literature specifically reporting on solo aging and depression is scant. Although there is little research examining the associations between depression and aging without a partner, close family or children, gerontological research has repeatedly reported a strong relationship between living alone and depression among older adults (Chen, Cui, Pan, Li, Waili, & Li, 2021; Fukunaga, Abe, Nakagawa, Koyama, Fujise, & Ikeda, M., 2021). Previous research indicates that older adults aging without a partner or living alone access more mental health services and are at higher risk for suicide (Sohn, 2012; Beghi et al., 2021; Dreyer et al., 2018). Further, most of the research examining factors related to solo aging and depression has relied on a self-report or brief measure of depression. The current study fills a significant gap in the literature because participants received the diagnosis of Major Depressive Disorder (MDD) by a geriatric psychiatrist, thus avoiding the possibility that individuals might self-report transient symptoms or subthreshold (minor) depression.

Gerontological literature suggests that living arrangements and the proximity of friends and family affect the amount of social support older adults receive, and confirm a strong relationship between greater social support and better mental health (Lubben & Gironda, 200; Zhou et al., 2018). Having a spouse in the same household may be a protective factor against various threats to well-being for both older men and women. For instance, studies have shown a higher incidence of depression among older adults who primarily eat their meals alone (e.g., Sakuri, Kawai, Suzuki, et al., 2021), something more common among unmarried older adults living alone and without close family members.

The association between social isolation and depression among community-dwelling older adults is well established in the gerontological literature (National Academies of Sciences, Engineering, and Medicine, 2020) including in a recent longitudinal study finding independent effects of social isolation on both Major Depression and Generalized Anxiety Disorder (Domènech-Abella, Mundó, Haro, & Rubio-Valera, 2019). As discussed above, solo agers are not necessarily socially isolated, but likely to be at greater risk for social isolation, particularly as they continue to age with functional limitations. Research also suggests that the effects of social disconnectedness and the experience of subjective social isolation may lead to diminished health and mental health, particularly depression (Fiordelli., 2020; Santini, Jose, Cornwall, et al., 2020). For solo agers, the risk of social disconnectedness, and this potential risk for developing depression, are especially relevant due to the lack of an intimate partner or close family members.

Purpose of the Current Study

To address an apparent gap in the extant literature, the current study examined associations between indicators of solo aging, frequency of reported loneliness, and diagnosis of MDD among community-dwelling older adults recruited for an observational study.

We hypothesized that the number of indicators of solo aging, specifically living alone, being unmarried, and lack of available close children, lack of available close siblings, and lack of available close friends would be associated with participants’ greater frequency of loneliness. Furthermore, based on a growing body of prior research noting the association social isolation and depressive symptoms, we hypothesized that the accumulation of those same aspects of solo aging would be associated with major depression in our sample of participants.

Methods

Data in this study were derived from the baseline of an ongoing multi-wave observational study of late-life depression among adults ages 60+, the Neurobiology of Late-life Depression (NBOLD) Study (Steffens, Manning, Wu, et al., 2015; Steffens, Wang, Manning & Pearlson, 2017). Depressed participants were recruited from outpatient psychiatry clinics at Hartford Hospital and from newspaper advertisements, whereas non-depressed “control” participants were recruited through advertisements and from a volunteer registry developed in the UConn Center on Aging in Connecticut. Inclusion criteria for all participants consisted of an initial Mini-Mental State Examination (MMSE) exam score of 25 or greater, no substance use disorder, other serious mental illness, or neurological disorders. The study was approved by the Institutional Review Boards of University of Connecticut and Hartford Hospital. All subjects were provided information about the study, including a review of the consent form, and then provided written, informed consent to participate. See Steffens, et al., (2015) for a complete description of study methodology.

Measures

Outcome Variables

Loneliness.

A one-item question taken from the CES-D Scale (Radloff et al., 1977) that asks respondents, during the past week, how often “I felt lonely” is used as the measure of loneliness in this study. The question offers four response categories: (1) No days lonely, (2) one or two days lonely, (3) three or four days lonely, and (4) five to seven days lonely. Because this original measure is ordinal and not a continuous frequency, the variable was dichotomized to represent two levels of loneliness: (1) Little or No Loneliness (responses 1 or 2) and (2) More Lonely Days (responses 3 or 4). Although not addressing this CES-D item expressly, Pinquart and Sorensen, in their classic meta-analysis (2001) reported that direct single-item frequency of loneliness questions were highly correlated with longer multi-item instruments, a finding recently corroborated by Mund, Maes, Drewke and colleagues (2021).

Depression Diagnosis.

Each participant underwent a thorough diagnostic interview to assess clinical depression status, including administration of the Montgomery-Asberg Depression Rating Scale (MADRS; Montgomery & Asberg,1979) by a study geriatric psychiatrist. Participants in the depressed group in the current study met criteria for Major Depressive Disorder (MDD).

Predictor Variables

Indicators of Solo Aging Risk.

The dataset we used included several characteristics associated with prevailing definitions of solo aging. These five dichotomous (yes or no) solo aging vulnerability factors we identified were as follows: 1) living alone, 2) unmarried status, 3) have no children, or no nearby or available children, 4) have no nearby or available siblings, and 5) have no nearby or available friends. Because each of these characteristics may be related to some of the others and to the concept of aging alone, or solo aging, and because it is not clear whether these can be ranked in importance (e.g., has greater impact on vulnerability), we opted to combine them into a composite “Solo Aging Indicators” in the study analyses. The Solo Aging Indicators score ranged from no aspects of solo aging to all five aspects, or from 0 to 5, with higher scores indicating more vulnerability, e.g. more aspects of solo aging.

Health Comorbidities.

The Cumulative Illness Rating Scale (CIRS) (Linn et al., 1988), as modified for geriatric patients (Miller et al., 1992), measured the sum of participants’ chronic conditions and the burden of these conditions upon the respondent. The measure rates fourteen illness areas (Heart; Vascular; Hematologic; Respiratory; Eyes, Ears, Nose, Throat; Upper G.I., Lower G.I., Liver; Renal; Genitourinary; Musculoskeletal; Neurological; Endocrine/Metabolic; Psychiatric/Behavioral) from 0 (no problem) to from 1 to 4 points (with examples of the level of illness burden for each) for a possible total of 56 points.

Demographics and Functioning.

The Duke Depression Evaluation Schedule (DDES, Landerman et al., 1989) was administered to each participant. Among other items, the DDES contains items covering demographic data. Variables drawn from the DDES for multivariate analysis in the current study include binary gender, age in years, and number of years of education, which we used as a proxy for having a college education and dichotomized at greater than or equal to 16 years of education (0 = less than college education; 1 = college education). Race was highly invariant, so we did not include it in the analyses.

Financial Difficulty.

The Duke Depression Evaluation Schedule (DDES, Landerman et al., 1989) also included one item measure of financial comfort with three levels that we dichotomized to financial comfort versus difficulty that was used as a measure of financial difficulty for this study. The item reads: Are your expenses so heavy that you cannot meet your payments, or you can meet your payments with some difficulty, or are your payments no problem to you? Those indicating they cannot meet payments or have some difficulty were categorized (0 = no financial difficulty; 1 = having financial difficulty).

Statistical Analysis

Univariate and bivariate analyses were first conducted on the solo aging-related variables of interest and potential demographic covariates available in the dataset. We calculated appropriate frequencies, means, etc., for each variable for the total sample and for separate groups based on diagnostic depression status (MDD or non-depressed). We obtained group comparisons with Chi-square coefficients or Independent Samples t-tests. Alpha was set at .05 for identifying significant between-group differences. We next fit separate multivariate logistic regression models on the measures of two outcomes of interest, loneliness and depression status. The likelihoods of frequent loneliness and a depression diagnosis were regressed on the same predictor variables and covariates in each model: female gender (ref = male), age in years, college education, financial difficulty, health comorbidities, and indicators of solo aging. Listwise deletion excluded cases with missing data for both the loneliness model (n = 4, 2.4%) and the depression model (n = 3, 1.8%).

Results

Description of the Sample

The complete sample consisted of 167 participants, 70.7% female, with a mean age of 72.4 years (SD = 7.5). Eighty-eight per cent of participants were white and the remaining 12% were a mix of African American, Asian Pacific Islander, and Latino/a. Education levels for the sample ranged from 15.8% with high school education only, to over half with a college degree and 37.6% with a graduate or professional degree. A majority (66.5%) were retired from regular employment, and 28.3% endorsed having some financial difficulty. Their CIRS health comorbidity scores averaged 5.02 (SD = 3.6).

In terms of the characteristics associated with solo aging, 52.1% of the full sample were unmarried/not partnered, while 43.1% lived alone. Although these two groups largely overlapped, 17 respondents who were unmarried also indicated living with other people, while two married respondents reported living alone. Regarding family and friend relationships, 41% of the sample had either no children or no available children nearby, 64.5% had no siblings nearby, and 18.7% had no friends available or nearby.

Depression status, based on a standardized clinical interview was as follows: 123 participants (73.7%) were diagnosed with Major Depressive Disorder (MDD), while 44 (26.3%) were determined to be non-depressed. The dichotomous loneliness variable found that 95 respondents (57.2%) were lonely zero to two days per week, whereas 71 (42.8%) were lonely three or more days a week. Table 1 presents additional details about the distribution of frequency of loneliness in the sample as well as descriptive statistics for other study variables.

Table 1.

Descriptive Statistics of Study Variables and Group Comparisons by Depression Status from a Case-Control Sample of Older Adult Outpatients (N = 167)

Variables Total Depression Status p
Non-depressed Depressed
n % M SD n % M SD n % M SD
Outcome Variables
Loneliness
   0 – 2 days/week   95 57.2
   3 – 7 days/week   71 42.8
Major Depression diagnosis 123 73.7
Predictor Variables
Female 118 70.7 33 75.0   85 69.1   .461
College education or greater 101 61.2 25 56.8   76 62.8   .485
Financial difficulty (Yes)   47 28.3   5 11.4   42 34.4   .004
Age (60-90) 167 72.4 7.5 44 75.0 7.2 123 71.5 7.4   .009
Health burden, CIRS (0-16) 167   5.0 3.6 44   2.7 2.1 124   5.9 3.6 <.001
Number of solo aging risksa (0-5) 166   2.2 1.3 44   1.8 1.3 122   2.3 1.3 .047
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Note. Differences in means for continuous variables were determined by Independent Samples t-tests; differences in categorical variables were determined using Chi-square goodness of fit tests.

a

Indicators of solo aging risk: (1) living alone, (2) being unmarried, (3) having no children, or no nearby or available children, (4) having no nearby or available siblings, and (5) having no nearby or available friends.

Bivariate Results

We conducted student t-tests or chi-square tests, as appropriate to the level of measurement, to determine non-controlled differences in the sample’s predictor variables (i.e., gender, age, college education, financial difficulty, comorbidities, and number of solo aging indictors) based on the study outcomes. The between group differences for depression are presented in Table 1. In this comparison, depressed participants were significantly younger, more likely to have financial difficulty, had higher medical comorbidity burden, and greater numbers of solo aging indicators. That the depressed group was significantly younger than the non-depressed, volunteer comparison group (with a mean difference of approximately three years) appears to be an artifact of the convenience sample used here.

The results for group differences based on low or high frequencies of loneliness were similar to those for depression status. Specifically, participants who reported feeling lonely three or more days per week were significantly younger (p = .036), more likely to have financial difficulty (p = .030), and had higher numbers of solo aging indicators (p < .001) than those who felt lonely two or fewer days per week. However, unlike depression, there were no significant differences based on comorbidity burden.

Multivariate Results

Frequency of Loneliness

Results of the logistic regression model for loneliness indicated there was a significant association between the predictor variables and the likelihood of feeling lonely three or more days per week (χ2(6) = 35.39, p < .001). The model correctly classified 67.5% of the total sample. Holding all other predictor variables constant, the odds of feeling lonely three or more days per week were significantly less for females (p = .08) and older participants (p = .01). Conversely, the odds of feeling lonely three or more times per week were doubled for each additional solo aging indicator present (OR = 2.05, p <.001, 95% CI OR [1.50, 2.80]). Having a college education, financial difficulty, and health comorbidities were not significant predictors of the likelihood of frequent loneliness. The final step in the model is shown in Table 2.

Table 2.

Factors Associated with Greater Frequency of Loneliness: Binary Logistical Regression of Final Step (N = 167)

Variable B S.E. Wald χ2 p OR 95% CI OR
Lower Upper
Sum of solo aging risksa 0.72 0.16 20.45 <.001 2.05 1.50 2.80
Female (ref = male) −0.74 0.43 2.98 .08 0.48 0.21 1.10
Age (in years) −0.07 0.03 6.67 .01 0.94 0.89 0.98
College education (ref = none) −0.62 0.38 2.62 .11 0.54 0.25 1.14
Financial difficulty (ref = none) 0.27 0.41 0.45 .50 1.31 0.59 2.93
Health burden (CIRS, 0-16) 0.02 0.05 0.22 .64 1.02 0.93 1.13
Constant 3.59 1.90 3.57 .06
Nagelkerkel R2 .262
Cox & Snell R2 .195
−2 LL 186.73
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Note. OR = Odds Ratio; CI = confidence interval.

a

Indicators of solo aging risk: (1) living alone, (2) being unmarried, (3) having no children, or no nearby or available children, (4) having no nearby or available siblings, and (5) having no nearby or available friends.

Major Depression Status

Results of the logistic regression model for depression indicated there was a significant association between the predictor variables and the likelihood of a diagnosis of major depressive disorder (χ2(6) = 59.66, p < .001). The model correctly classified 79.3% of the total sample. Older participants were less likely to be diagnosed with depression (p = .001). Holding all other predictors constant, the odds of being diagnosed with depression were approximately three times higher for those with financial difficulty (OR = 2.96, p = .06, 95% CI [0.94, 9.30]), and increased by approximately 50% with each additional solo aging indicator (OR = 1.47, p = .03, 95% CI [1.04, 2.07]). Health comorbidity status was also positively associated with the likelihood of a depression diagnosis (OR = 1.7, p < .001, 95% CI [1.36, 2.13]). Gender and having a college education were not significantly associated with the likelihood of a depression diagnosis. The final step in the model is shown in Table 3.

Table 3.

Factors Associated with Greater Likelihood of Major Depression Diagnosis: Binary Logistical Regression of Final Step (N = 167)

Variable B S.E. Wald χ2 P OR 95% CI OR
Lower Upper
Sum of solo aging risksa 0.38 0.18 4.71 .03 1.47 1.04 2.07
Female (ref = male) −0.71 0.53 1.81 .18 0.49 0.17 1.38
Age (in years) −0.11 0.03 10.63 .001 0.90 0.84 0.96
College education (ref = none) 0.33 0.45 0.54 .46 1.40 0.57 3.40
Financial difficulty (ref = none) 1.09 0.58 3.46 .06 2.96 0.94 9.30
Health burden (CIRS, 0-16) 0.53 0.11 21.70 <.001 1.70 1.36 2.13
Constant 6.01 2.39 6.31 .01
Nagelkerkel R2 .444
Cox & Snell R2 .305
−2 LL 131.09
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Note. OR = Odds Ratio; CI = confidence interval.

a

Indicators of solo aging risk: (1) living alone, (2) being unmarried, (3) having no children, or no nearby or available children, (4) having no nearby or available siblings, and (5) having no nearby or available friends.

Discussion

In light of the increasing number of older adults who are or may soon be solo agers, this study built on a previous study that determined the high prevalence of solo agers who are at high risk for becoming vulnerable solo agers (Carney et. al, 2016). We examined the associations of risks for vulnerable solo ager status (e.g., living alone, childlessness, and lack of close family or friendships) with frequency of loneliness and diagnosis of MDD (versus non-depressed controls) in a convenience case/control sample of adults over age 60.

This study is one of the first to examine the solo aging phenomenon in relation to loneliness and depression. A contribution of this study is the finding that the number of Solo Aging indicators was associated with frequency of loneliness, and with the diagnosis of MDD, supporting prior literature on the risks associated with social isolation (Choi, Irwin & Cho, 2015; Blazer, 2020), and with living alone (Fukunaga, et al., 2021) in later life. Further, it is noteworthy that, as in prior studies (Warner, Adams, & Roberts, 2017; Moon, Adams & Roberts, 2012; Adams et al., 2004), this study identified two primary factors associated with a diagnosis of depression. The first was social privations, e.g. the number of solo aging indicators, and the second was poorer health, here as measured by the CIRS illness burdens scale.

A growing body of research demonstrates that experiencing loneliness is strongly associated with depression among older adults (Adams, Sanders & Auth, 2004; Barg, Huss-Ashmore, Wittink, Murray, Bogner & Gallo, 2006; Cohen-Mansfield & Parpura-Gill, 2007; Gonyea, Curley, Melekis, Levine & Lee, 2018; Luanaigh & Lawlor, 2008; Warner, et al., 2017). Prior studies have found that loneliness has independent effects on depression over time (e.g., Cacioppo, Hawkley & Thisted, 2010), including a recent study that used data from the English Longitudinal Study of Ageing (Lee, Pearce, Ajnakina, et al., 2021). The current study looked at the associations of solo aging with loneliness and depression separately, but future research might be designed to more formally test the theoretical pathway from indicators of solo aging to the experience of loneliness and to the outcome of depressive symptoms.

Foremost among the strengths of this study was the careful diagnostic process in which a geriatric psychiatrist identified those participants with MDD and those participants who were non-depressed. The study also benefitted from the comprehensive measures of available kin relationships and living situation that were available in the dataset and allowed us to create a composite Solo Aging Indicator score.

Several limitations of this study should also be noted. A primary limitation of the study is the non-equivalence of the two groups resulting from the convenience, case/control study design, although controls in the multivariate analyses ameliorate non-equivalence to an extent. Further, the relatively small number of control participants in comparison to those diagnosed with major depression and the overall number of participants limits the statistical power to detect true group differences. And finally, the sample was from one geographic location; thus, the findings may not be generalizable, particularly to communities with greater ethnic and gender diversity.

Another limitation of the study is the single-item variable used to define loneliness, although the use of this type of single-item loneliness measure has been shown to be reliable and valid by other researchers (Pinquart & Sorensen, 2001; Mund, Maes, Drewke, et al., 2021). Future research may benefit from the use of an established multi-item loneliness scale. Finally, as with any secondary analysis of data gathered for a different purpose, there are limitations in the level of detail available. For instance, living alone is a primary indicator of solo aging throughout the literature, but knowing how long the respondents have been living alone might provide a more nuanced understanding of its significance later in life.

Overall, results from this study contribute to the literature on risk factors for loneliness and depression among community-based older adult populations, many who are aging alone, particularly at more advanced ages, providing valuable insights into the needs of one of the fastest-growing segments of the older adult population. Although further research is needed, geriatric providers should be aware of the increased risks for loneliness and depression among older adults who are living alone and have few or no close family and/or close friendships.

Our findings suggest that intervention in both the physical (e.g., health screenings, promoting healthy lifestyles to reduce the burden of chronic conditions, enabling access to good medical care) and collective arenas (e.g. providing opportunities for social connections and support), may be important in preventing or reducing loneliness and symptoms of depression. The latter might include programming and outreach by senior and community centers that facilitates the participation of older adults living alone (Cornwell, Laumann & Schumm, 2008).

What this paper adds to existing literature:

Point 1: Solo agers are an understudied group

Point 2: The study uses secondary data in which a geriatric psychiatrist diagnosed the depression cases

Point 3: Findings of the study point to future areas for research in terms of associations of the cumulative aspects of solo aging with both loneliness and depression.

What this paper adds to gerontological practice:

Point 1: Practitioners need to be aware of older adults’ living situation and support network when offering advice or treatments.

Point 2: Solo agers, particularly those at advanced ages, may be at greater risk for both loneliness and depression.

Point 3: Facilitating group participation may be a useful strategy in preventing loneliness and depression among older adults who live alone and lack close family members.

Acknowledgments

Funded by National Institutes of Mental Health R01(MH096725) and P30 (AG067988). The NBOLD study was approved by the Institutional Review Boards of UCHC and Hartford Hospital. All subjects were provided information about the study, including a review of the consent form, and then provided written, informed consent to participate.

NIMH funded R01 grant entitled “Neurobiology and Adverse Outcomes of Neuroticism in Late-life Depression” (MH096725) at the University of Connecticut Health Center (UCHC) and the Olin Neuropsychiatry Research Center at the Institute of Living at Hartford Hospital.

Footnotes

The authors of this manuscript report no conflict of interest.

An earlier version of this manuscript was presented at the Gerontological Society of America Annual Meeting, Boston, November, 2018.

References

  1. Adams KB, Sanders S & Auth EA (2004). Loneliness and depression in independent living retirement communities: Risk and resilience factors. Aging and Mental Health, 8(6), pp. 475–85. [DOI] [PubMed] [Google Scholar]
  2. Adams KB, Leibbrandt S & Moon H (2011). A critical review of the recent literature on activity and wellbeing in later life. Ageing and Society, 31, 683–712. DOI: 10.1017/S0144686X10001091 [DOI] [Google Scholar]
  3. Administration for Community Living. (2018). Aging and Disability in America. Retrieved from https://www.acl.gov/sites/default/files/Aging%20and%20Disability%20in%20America/2017OlderAmericansProfile.pdf
  4. Barg FK, Huss-Ashmore R, Wittink MN, Murray GF, Bogner HR, Gallo JJ (2006). A mixed-methods approach to understanding loneliness and depression. Journal of Gerontology, Series A: Social Sciences, 61, S329–S339. [DOI] [PMC free article] [PubMed] [Google Scholar]
  5. Beghi M, Butera E, Cerri CG, Cornaggia CM, Febbo F, Mollica A, … & Lozupone M (2021). Suicidal behaviour in older age: A systematic review of risk factors associated to suicide attempts and completed suicides. Neuroscience & Biobehavioral Reviews, 127, 193–211. [DOI] [PubMed] [Google Scholar]
  6. Blazer D (2020). Social Isolation and loneliness in older adults—A mental health/public health challenge. Journal of the American Medical Association: Psychiatry, 77(10). [DOI] [PubMed] [Google Scholar]
  7. Bookwala J, Marshall KI, & Manning SW (2014). Who needs a friend? Marital status transitions and physical health outcomes in later life. Health Psychology, 33(6), 505–515. 10.1037/hea0000049 [DOI] [PubMed] [Google Scholar]
  8. Cacioppo JT, Hawkley LC, & Thisted RA (2010). Perceived social isolation makes me sad: 5-year cross-lagged analyses of loneliness and depressive symptomatology in the Chicago Health, Aging, and Social Relations Study. Psychology and aging, 25(2), 453–63. [DOI] [PMC free article] [PubMed] [Google Scholar]
  9. Camp LJ, & Peterson M (2018). Meeting the challenge of a new generation of solo agers. Bifocal, 39(3), 34. [Google Scholar]
  10. Carney MT, Fujiwara J, Emmert BE Jr., Liberman TA & Paris B (2016). Elder orphans hiding in plain sight: A growing vulnerable population. Current Gerontology and Geriatrics Research, Volume 2016, Article ID# 4723250, 11 pages. [DOI] [PMC free article] [PubMed] [Google Scholar]
  11. Chen Y, Cui PY, Pan YY, Li YX, Waili N, & Li Y (2021). Association between housing environment and depressive symptoms among older people: a multidimensional assessment. BMC geriatrics, 21(1), 1–10. [DOI] [PMC free article] [PubMed] [Google Scholar]
  12. Choi H, Irwin MR, & Cho HJ (2015). Impact of social isolation on behavioral health in elderly: Systematic review. World Journal of Psychiatry, 5(4), 432. doi: 10.5498/wjp.v5.i4.432 [DOI] [PMC free article] [PubMed] [Google Scholar]
  13. Cohen-Mansfield J and Parpura-Gill A (2007). Loneliness in older persons: a theoretical model and empirical findings. International Psychogeriatrics, 19, 279–294. [DOI] [PubMed] [Google Scholar]
  14. Cohen-Mansfield J, Hazan H Lerman Y & Shalom V (2015). Correlates and predictors of loneliness in older adults: A review of quantitative results informed by qualitative insights. International Psychogeriatrics, 28, 4. [DOI] [PubMed] [Google Scholar]
  15. Cornwell B, Laumann EO, & Schumm LP (2008). The social connectedness of older adults: A national profile. American sociological review, 73(2), 185–203. [DOI] [PMC free article] [PubMed] [Google Scholar]
  16. Djundeva M, Dykstra P, & Fokkema T (2019). Is living alone “aging alone”? Solitary living, network types, and well-being. The Journals of Gerontology: Series B, Psychological Sciences and Social Sciences, 74(8), 1406–1415. doi: 10.1093/geronb/gby119 [DOI] [PMC free article] [PubMed] [Google Scholar]
  17. Domènech-Abella J, Mundó J, Haro JM, & Rubio-Valera M (2019). Anxiety, depression, loneliness and social network in the elderly: Longitudinal associations from The Irish Longitudinal Study on Ageing (TILDA). Journal of affective disorders, 246, 82–88. [DOI] [PubMed] [Google Scholar]
  18. Dreyer K, Steventon A, Fisher R, & Deeny SR (2018). The association between living alone and health care utilisation in older adults: a retrospective cohort study of electronic health records from a London general practice. BMC geriatrics, 18(1), 1–7. [DOI] [PMC free article] [PubMed] [Google Scholar]
  19. Eshbaugh EM. (2009). The role of friends in predicting loneliness among older women living alone. Journal of Gerontological Nursing, 35(5), 13–6. doi: 10.3928/00989134-20090331-03. [DOI] [PubMed] [Google Scholar]
  20. Fiordelli M, Sak G, Guggiari B, Schulz PJ, & Petrocchi S (2020). Differentiating objective and subjective dimensions of social isolation and appraising their relations with physical and mental health in italian older adults. BMC geriatrics, 20(1), 1–13. [DOI] [PMC free article] [PubMed] [Google Scholar]
  21. Fukunaga R, Abe Y, Nakagawa Y, Koyama A, Fujise N, & Ikeda M (2012). Living alone is associated with depression among the elderly in a rural community in Japan. Psychogeriatrics, 12(3), 179–185. [DOI] [PubMed] [Google Scholar]
  22. Gonyea JG, Curley A, Melekis K, Levine N, & Lee Y (2018). Loneliness and depression among older adults in urban subsidized housing. Journal of Aging and Health, 30(3), 458–474. [DOI] [PubMed] [Google Scholar]
  23. Ianzito C (2017) Elder orphans: How to plan for aging without a family caregiver [Web log post]. Retrieved from http://www.aarp.org/home-family/caregiving/info-2016/caregiving-tips-when-aging-alone.html?intcmp=CRC-FEED
  24. Kim J-I, Choe M-A, Chae YR (2009). Prevalence and predictors of geriatric depression in community-dwelling elderly. Asian Nursing Research, 3(3), pp.121–129. 10.1016/S1976-1317(09)60023-2 [DOI] [PubMed] [Google Scholar]
  25. Landerman R, George LK, Campbell RT & Blazer DG (1989). Alternative models of the stress buffering hypothesis. American Journal of Community Psychology, 1(17), pp. 626–642. [DOI] [PubMed] [Google Scholar]
  26. Lee SL, Pearce E, Ajnakina O, Johnson S, Lewis G, Mann F, … & Lewis G (2021). The association between loneliness and depressive symptoms among adults aged 50 years and older: a 12-year population-based cohort study. The Lancet Psychiatry, 8(1), 48–57. [DOI] [PMC free article] [PubMed] [Google Scholar]
  27. Lin IF, & Brown SL (2012). Unmarried boomers confront old age: A national portrait. The Gerontologist, 52(2), 153–165. doi: 10.1093/geront/gnr141 [DOI] [PMC free article] [PubMed] [Google Scholar]
  28. Linn BS, Linn MW & Gurel L (1988). Cumulative Illness Rating Scale. Journal of the American Geriatrics Society, 16, pp. 622–626. [DOI] [PubMed] [Google Scholar]
  29. Lubben J, & Gironda M (2004). Measuring social networks and assessing their benefits. Social networks and social exclusion: Sociological and policy perspectives, 20–34. [Google Scholar]
  30. Luanaigh CÓ, & Lawlor BA (2008). Loneliness and the health of older people. International Journal of Geriatric Psychiatry: A journal of the psychiatry of late life and allied sciences, 23(12), 1213–1221. [DOI] [PubMed] [Google Scholar]
  31. Marak C (2017). The aging & alone care needs & preferences. Today’s Caregiver, 22–23. [Google Scholar]
  32. Margolis R, & Verdery AM (2017). Older adults without close kin in the United States. The Journals of Gerontology Series B, Psychological Sciences and Social Sciences, 72(4), 688–693. [DOI] [PMC free article] [PubMed] [Google Scholar]
  33. Martín-María N, Caballero FF, Lara E, Domènech-Abella J, Haro JM, Olaya B, … & Miret M (2021). Effects of transient and chronic loneliness on major depression in older adults: a longitudinal study. International Journal of Geriatric Psychiatry, 36(1), 76–85. [DOI] [PubMed] [Google Scholar]
  34. Miller MD, et al. (1992). Rating chronic medical illness burden in geropsychiatric practice and research: application of the Cumulative Illness Rating Scale. Psychiatry Research, 41, pp. 237–248. [DOI] [PubMed] [Google Scholar]
  35. Montgomery SA & Asberg M (1979). A new depression scale designed to be sensitive to change. British Journal of Psychiatry, 134, pp.382–389. [DOI] [PubMed] [Google Scholar]
  36. Moon H, Adams KB & Roberts AR (2012). Risk factors for depression among the oldest old in urban congregate housing: Contribution of grief. International Social Work, DOI: 10.1177/0020872811429954 [DOI] [Google Scholar]
  37. Mund M, Maes M, Drewke PM, Gutzeit A, Jaki I, & Qualter P (2021). Would the Real Loneliness Please Stand Up? The Validity of Loneliness Measures and the Reliability of Single Items. [DOI] [PMC free article] [PubMed] [Google Scholar]
  38. National Academies of Sciences, Engineering, and Medicine. (2020). Social isolation and loneliness in older adults: Opportunities for the health care system. National Academies Press. [PubMed] [Google Scholar]
  39. O’Rourke H & Sidani S (2017). Definition, Determinants, and Outcomes of Social Connectedness for Older Adults: A Scoping Review. Journal of Gerontological Nursing, 43(07), pp. 1–10. [DOI] [PubMed] [Google Scholar]
  40. Pinquart M (2003). Loneliness in married, widowed, divorced, and never-married older adults. Journal of Social and Personal Relationships, 20(1), 31–53. doi: 10.1177/026540750302002 [DOI] [Google Scholar]
  41. Pinquart M, & Sorensen S (2001). Influences on loneliness in older adults: A meta-analysis. Basic and applied social psychology, 23(4), 245–266. [Google Scholar]
  42. Portacolone E, Johnson JK, Halpern J & Kotwal A (2020). Seeking a sense of belonging. Generations Journal, 44(3), Fall. [PMC free article] [PubMed] [Google Scholar]
  43. Radloff LS (1977). The CES-D scale: A self-report depression scale for research in the general population. Applied Psychological Measurement, 1(3), pp. 385–401. [Google Scholar]
  44. Sakurai R, Kawai H, Suzuki H, Kim H, Watanabe Y, Hirano H, … & Fujiwara Y (2021). Association of eating alone with depression among older adults living alone: Role of poor social networks. Journal of Epidemiology, 31(4), 297–300. [DOI] [PMC free article] [PubMed] [Google Scholar]
  45. Santini ZI, Jose PE, Cornwell EY, Koyanagi A, Nielsen L, Hinrichsen C, … & Koushede V (2020). Social disconnectedness, perceived isolation, and symptoms of depression and anxiety among older Americans (NSHAP): a longitudinal mediation analysis. The Lancet Public Health, 5(1), e62–e70. [DOI] [PubMed] [Google Scholar]
  46. Schlecht A (2018). More people aging alone as “elder orphans.” The Olympian. Retrieved from http://www.theolympian.com/news/local/article192820524.html [Google Scholar]
  47. Shankar A, McMunn A, Banks J, & Steptoe A (2011). Loneliness, social isolation, and behavioral and biological health indicators in older adults. Health Psychology, 30(4), 377–385. doi: 10.1037/a0022826 [DOI] [PubMed] [Google Scholar]
  48. Sohn JN (2012). A study on factors influencing the suicidal ideation in elderly people who live alone or live with family. Journal of Korean Academy of Psychiatric and Mental Health Nursing, 21(2), 118–126. [Google Scholar]
  49. Steffens DS, Manning KJ, Wu R, Grady JJ, Fortinsky RF & Tennen HA (2015). Methodology and preliminary results from the Neurobiology of Late-life Depression Study, International Psychogeriatrics, 27(12), pp. 1987–1997. doi: 10.1017/S1041610215001386. [DOI] [PMC free article] [PubMed] [Google Scholar]
  50. Steffens DS, Wang L, Manning KJ & Pearlson GD (2017). Negative affectivity, aging, and depression: Results from the Neurobiology of Late-Life Depression (NBOLD) Study. American Journal of Geriatric Psychiatry; 25, pp. 1135–1149. [DOI] [PMC free article] [PubMed] [Google Scholar]
  51. Taylor HO, Taylor RJ, Nguyen AW & Chatters L (2018). Social Isolation, Depression, and Psychological Distress Among Older Adults, Journal of Aging and Health, 30(2), pp. 229–246. doi: 10.1177/0898264316673511 [DOI] [PMC free article] [PubMed] [Google Scholar]
  52. Victor C, Scambler S, Bond J, & Bowling A (2000). Being alone in later life: Loneliness, social isolation and living alone. Reviews in Clinical Gerontology, 10(4), 407–417. doi: 10.1017/S0959259800104101 [DOI] [Google Scholar]
  53. Warner CB, Adams KB & Roberts AR (2017). Coping resources, loneliness and depression of older women with chronic illness. Journal of Applied Gerontology, 38(3), pp. 295–322 [DOI] [PubMed] [Google Scholar]
  54. Weiss RS (1984). Loneliness: What we know about it and what we might do about it. In Peplau LA & Goldston SE (Eds.), Preventing the harmful consequences of severe and persistent loneliness (pp. 3–12). National Institute of Mental Health. [Google Scholar]
  55. Weissman MM, Sholomskas D, Pottenger M, Prusoff BA & Locke BZ (1977). Assessing depressive symptoms in five psychiatric populations: a validation study. American Journal of Epidemiology, 106, pp. 203–214. [DOI] [PubMed] [Google Scholar]
  56. Zhou Z, Mao F, Ma J, Hao S, Qian Z, Elder K, … & Fang Y (2018). A longitudinal analysis of the association between living arrangements and health among older adults in China. Research on Aging, 40(1), 72–97. [DOI] [PubMed] [Google Scholar]

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