Solo but not alone: An examination of social and help networks among community-dwelling older adults without close family

Abstract

This study evaluates help sources for personal and health tasks of adults living in the community without a spouse or nearby children. Using data from the National Health and Aging Trends Study (NHATS), a nationally representative sample of Medicare beneficiaries ages 65 and over, we conducted a population-based study of 2,998 community-dwelling adults who received assistance with personal, household, or medical tasks in the past month. Using ANOVA, we compared adults aging solo to those with spouses at home and/or children in the same state. Adults aging solo were significantly more likely to identify non-child/spouse family, friends, neighbors and paid aides as part of their social networks. Their sources of unpaid help included siblings (33%), friends (32%), and non-family (e.g., neighbors (23%)). Adults aging solo were more likely to use paid caregivers, despite having lower incomes than married peers. Interventions to support adults aging solo should incorporate diverse social/help networks.

Background

Shifting demographics, such as lower birth rates, divorce, and geographic dispersion of families are challenging historical presumptions that older adults have family caregivers (spouse/partner or adult children) available nearby (Freedman & Wolff, 2020; Verdery et al., 2019). Nearly one in four adults is at high risk for aging without a spouse or children (Carney et al., 2016; Chamberlain et al., 2018; Farrell et al., 2017; Roofeh et al., 2020).

Lack of family/friend or other unpaid caregivers correlates to disparate access to care and outcomes: Single, divorced, or widowed adults face longer hospital stays and higher readmissions rates than those who are married, as hospitals may require at-home caregivers for discharge (Adisa et al., 2018; Konda et al., 2020; Lu et al., 2016). Older adults living alone are less likely to die at home rather than in a nursing home or hospice facility than those living in larger households (Lei et al., 2021), suggesting that at-home help bolsters ability to live in community.

Previous descriptions of adults aging solo have focused on social isolation (Chamberlain et al., 2018; Roofeh et al., 2020), yet diverse, non-kin social networks can provide robust emotional and instrumental (task-oriented) support and such networks are becoming more common over time (Suanet & Antonucci, 2016; Verdery et al., 2019), although the type and intensity of support may vary by the type of relationship (e.g., kin vs non-kin) and factors including frequency of interaction (Wellman 1990). Accordingly, older adults with and without nearby close kin may differ in their social networks and available instrumental supports, yet little is known about whether more diverse social networks translate to sources of help that could help adults aging solo preserve their ability to live independently. Therefore, as a first step, we sought to define the population of adults aging solo and compare its social networks and sources of help to adults with close family nearby.

Methods

Data and sample:

We used data from 2015 National Health and Aging Trends Study (NHATS), a nationally representative, longitudinal study of late-life disability and function among 8.334 Medicare beneficiaries ages 65 and older based on annual interviews with participants and proxies. The NHATS sample was replenished in 2015, making this wave the largest recent sample. We included community-dwelling adults who completed the survey without help from a proxy and had received help in the past month with at least one instrumental activity of daily living (IADL); activity of daily living (ADL); or medical issue. We excluded those living in assisted living or skilled nursing facilities where such help might be provided by staff. We compared demographic characteristics, social network size and composition, and help received for each group (Figure 1, Sample Derivation).

Figure 1.

Sample Derivation

To determine whether adults aging solo differed from peers with spouses and/or nearby children, we compared social networks and sources of help for adults in four categories: 1) Married-Children Nearby (residing with spouse and having children in the same state), 2) Married-No Children (residing with spouse and no nearby children), 3) Unmarried-Children Nearby (with children nearby but no spouse), and 4) Aging Solo (with neither spouse nor nearby children). We chose to separate individuals with/without spouses and children into distinct groups rather than aggregate a single “with family nearby” category to better capture how presence or absence of these relationships might correlate to nuanced differences in social and help networks. We focused on help received, as opposed to help needed, with the assumption that receiving help is a facilitator to remaining independent in the community.

Measures:

Our key variables of interest are the size and composition of social networks and help networks. Social networks are identified in NHATS by asking, “Looking back over the last year, who are the people you talked with most often about important things?” We grouped relationships into five categories: 1) “Spouse/partner/boyfriend/girlfriend”; 2) “Child/Child’s spouse/stepchild”; 3) “Other family (including any of the following: sibling, grandchild, niece/nephew, other family)”; 4) “Friend”; and 5) “Other (including any of the following: renter/roommate, neighbor, clergy, ex-wife/ex-husband, other non-relative).”

To identify help received, we grouped IADLs (laundry, shopping, cooking or paying bills), ADLs (eating, bathing, toileting, dressing, getting out of bed, getting around inside, getting around outside), and help with medical issues (managing medication, attending medical appointment)) as forms of care. Participants identified the relationship of the person providing help, which we grouped as in the social network categories. Help was defined as paid if it was provided by a paid aide/housekeeper/employee, and unpaid if it was provided by a non-relative or family member. Because residents of nursing homes and other facilities were excluded, care provided by staff in these settings also is excluded. The number of unique caregivers was defined as the number of unique social roles listed as sources of help for all help received.

Analytic strategy:

We calculated summary statistics for each group. No single variable had >5% missing data except “Has children living in the same city” and “Number of children in the same city” (each 6.3% missing), therefore univariate descriptive results were presented with missing values dropped. We used NHATS sampling weights to account for complex survey design and sampling strategy (Freedman et al., 2020). We used ANOVA to compare differences (95% CI) among the four subgroups. All analyses were performed using Stata Version 17 (StataCorp).

Results

Among 8,334 participants in the 2015 survey, 7,093 were self-responders and 6,931 of those were community-dwelling (Figure 1). We examined characteristics of 2,998 community-dwelling adults who were able to self-respond to survey questions and received help with at least one household, self-care, or medical management issue in the past month. Among these we identified four groups based on availability of close family members who could potentially serve as unpaid caregivers (Table 1): 1) Married-Children Nearby (N=1,278, 43%); 2) Married-No Children (N=247, 8%); 3) Single-Children Nearby (N=1,243, 41%); 4) Aging Solo (N=230, 8%).

Table 1:

Demographic characteristics of groups of older adults by family proximity (weighted)

Demographics	Married-Children Nearby %	Married-No Children %	Single-Children Nearby %	Aging Solo %	Total %	p-val (1&4)	p-val (2&4)	p-val (3&4)
Female	41.0%	36.2%	80.1%	56.9%	54.1%	<.01	<.01	<.01
Age (mean, SD)	74.18 (5.96)	74.99	79.82	77.21	76.26 (7.78)	<.01	0.01	<.01
Race, categorical						<.01	<.01	0.46
White Non-Hispanic	77.3%	82.1%	69.7%	62.4%	74.3%
Black Non-Hispanic	5.7%	6.0%	13.3%	14.7%	8.8%
Other (Am Indian/Asian/N at. Hawaii)	4.7%	**	4.0%	**	4.7%
Hispanic	9.1%	**	10.3%	**	9.3%
Missing	3.2%	**	2.8%	**	2.9%
Married	96.1%	**	1.7%	**	59.2%	<.01	<.01	0.55
Lives with spouse/partner	99.6%	99.9%	0.00%	0.00%	61.3%	<.01	<.01	NA
Separated or divorced	**	**	23.5%	34.9%	9.9%	<.01	<.01	0.01
Widowed	**	**	72.3%	36.6%	25.6%	<.01	<.01	<.01
Never married	**	**	2.5%	26.6%	2.6%	<.01	<.01	<.01
Number of household members (median, IQR)	2.00 (2.00–2.00)	2.00 (2.00–2.00)	1.00 (1.00–3.00)	1.00 (1.00–1.00)	2.00 (2.00–2.00)	<.01	<.01	<.01
Estimated yearly income						<.01	<.01	0.03
<$30,000	27.6%	20.5%	77.9%	67.4%	45.6%
$30,000–<$43,000	17.5%	22.1%	8.8%	13.3%	14.9%
$43,000–<$66,000	23.0%	17.0%	7.9%	13.8%	17.0%
$66,000 or more	32.0%	40.5%	5.4%	5.2%	22.5%
Number of self-reported comorbidities	3.21 (1.55)	2.66 (1.67)	3.67 (2.12)	3.23 (1.79)	3.31 (1.79)	0.90	0.01	0.01
Children
Number of living children (including spouse’s child, stepchild) (mean, SD)	3.46 (1.64)	1.74 (1.69)	3.73 (2.49)	1.04 (1.62)	3.23 (2.08)	<.01	<.01	<.01
Has children living in same city	58.8%	0.00%	75.3%	0.00%	54.8%	<.01	NA	<.01
Number of children in same city (mean, SD)	1.02 (1.10)	0.00 (0.00)	1.47 (1.52)	0.00 (0.00)	1.07 (1.27)	<.01	NA	<.01

Compared with married groups (married with children nearby and without children nearby), adults aging solo were more likely to be Black non-Hispanic, to be female, and to have lower incomes than married peers (p<.01) (Table 1). Sixty percent of adults aging solo were divorced or never married, compared with 26% of Single-Children Nearby (p<.01). There were no significant differences across groups in social network size, but relative to each of the three comparator groups, adults aging solo were significantly more likely to include other family and friends, among their social networks (p<.01) (Table 2). Twenty-two percent of adults aging solo included children living out-of-state in their social networks.

Table 2:

Social Network Size and Composition

Social Network	Married-Children Nearby	Married-No Children	Single-Children Nearby	Aging Solo	Total	p-val (1&4)	p-val (2&4)	p-val (3&4)
Number in social network (mean, SD)	2.16 (1.19)	2.07 (1.27)	2.20 (1.44)	1.97 (1.40)	2.15 (1.31)	0.12	0.55	0.07
Percent (N) of group members listing [role] as someone in their social network:
Spouse/partner/boy/girlfriend	83%	86.3%	**	**	51.9%	<.01	<.01	0.18
Child/child’s spouse/stepchild	42.8%	19.9%	79%	22.5%	51%	<.01	0.55	<.01
Other family (inc. any of the following: sibling, grandchild, niece/nephew, other family)	20%	29.2%	26.2%	51.7%	24.9%	<.01	<.01	<.01
Friend	16.3%	22.1%	21%	37.8%	19.7%	<.01	<.01	<.01
Other (e.g., renter/ roommate, paid aide, neighbor, clergy)	6.1%	9%	8.9%	14.1%	7.8%	<.01	0.20	0.04
Number of unique individuals providing care in past month (unpaid) (mean, SD)	1.69 (0.91)	1.32 (0.58)	2.18 (1.37)	1.63 (1.16)	1.81 (1.08)	0.49	<.01	<.01
Number of unique individuals providing care in past month (all) (mean, SD)	1.81 (0.99)	1.39 (0.69)	2.45 (1.49)	2.18 (1.25)	2.00 (1.20)	<.01	<.01	<.01

More than half of adults aging solo (55%) reported receiving help with independent activities of daily living (IADL), such as shopping or cooking, in the past month, and 43% received help with at least one activity of daily living (ADL), such as bathing or dressing. Across all groups, adults aging solo were least likely to report having a caregiver attend medical visits or help with medication (71%), compared to 78–86% in other groups. Adults aging solo were more than twice as likely to use paid help than other groups (33% vs 16% for Single-Children Nearby) (p<.01) despite having lower incomes than married peers, and significantly less likely to receive unpaid help with IADLs and medical activities but not ADLs. (See Appendix Tables A1, A2)

While some types of assistance for adults aging solo, particularly ADLs, were completed by either paid aides or unpaid caregivers, IADLs, such as help with financial matters, and medical activities were more likely to be performed by unpaid helpers (Figure 2).

Figure 2:

Percent of adults aging solo receiving paid and unpaid help, by activity (weighted %)

Spouses performed more than 95% of unpaid helping tasks among married individuals. For the Single-Children Nearby group, children performed 87% of unpaid helping tasks. In contrast, adults aging solo reported a diverse network of unpaid caregivers: 33% of unique help tasks were performed by siblings, 32% by friends, 23% by non-family individuals such as neighbors, and 16% by nieces or nephews (Appendix Table A3).

Discussion

We demonstrate that adults aging solo (i.e., those without a spouse/partner or children in the same state) who receive help with help tasks have social and caregiving networks of similar size but greater heterogeneity than those of peers who have a spouse and/or nearby children. Further, adults aging solo rely on paid aides at much higher rates than those with spouses, despite having lower household incomes.

Our analyses suggest that there are both strengths and potential vulnerabilities for individuals aging without traditional family support systems. Their diverse support network could be an asset, as adults aging solo may have more potential sources of care. However, friends and siblings are the most common sources of unpaid help for this group; caregivers in the same age group may have help needs of their own and may therefore become less able over time to provide help. Adults aging solo were the least likely to have a caregiver assist with medical needs, such as attending appointments, which could reduce their ability to live independently with chronic medical conditions; 68% of Medicare beneficiaries have two or more chronic conditions (Lochner & Cox, 2013).

This study builds on previous analyses focused on “kinless” adults by shifting the focus from social isolation to identify ways that older adults without spouses or children leverage social connections to address help needs while living independently. Such findings could become the basis of interventions to help adults aging solo strengthen social networks that reduce isolation and facilitate unpaid caregiving, as well as policy change to support non-traditional caregivers and promote equitable health outcomes.

This study has several limitations. Categories (i.e., marital status, location of children) are not necessarily fixed. While 27% of adults aging solo were never married, 36% were widowed and 35% were divorced and may recently have occupied one of the married groups; data are self-reported. “People you talked with most often about important things” is not a comprehensive measure of who is in a social network; neighbors may not share emotional closeness yet still help with small tasks due to proximity (Wellman & Wortley, 1990). We categorized paid (hired) vs unpaid help as a dichotomous variable; however, some states offer family members renumeration for caregiving. Because of small sample sizes, we were unable to assess whether adults aging solo vary in social network size and composition based on more specific marital history (e.g., never married vs widowed) or gender. For example, adults who never married or divorced young may have cultivated a broader social network over a lifetime than someone who socialized primarily with a spouse before being widowed or divorced late in life (Stokes & Moorman, 2018). Further, women may live longer but have fewer financial resources after widowhood than men, which may lead to differential access to caregiving and different relationships with social networks (Freak-Poli et al., 2022); future research could analyze help networks and life trajectories of adults aging solo by gender. Defining “nearby children” as those living within the same state is an imprecise approximation of a child’s geographic proximity to a parent and does not take into account relationship quality or estrangement. Viewing the groups at a single timepoint also obscures potentially meaningful trends in health and functional independence: Adults without a close primary caregiver may be less able to remain independent with cardiovascular disease, for example, and may move to institutional living earlier than someone residing with a spouse. We did not conduct subanalyses by health status or age group, which may correlate to social network size; for example, Kristensen et al (Kristensen et al., 2021) found in a study of Danish decedents that 7% with cancer were kinless, compared with 11% with cardiovascular disease. Finally, the study looks only at people who received help with IADLs, ADLs, medication management or medical appointments in the past month; it does not account for those who needed but did not receive any help, which may include individuals experiencing true social isolation.

While epidemiological data can pinpoint what help is provided and by whom, they leave unexplored the interpersonal, social, economic, and policy-driven forces that mediate and moderate those caregiving exchanges (Talley & Crews, 2007) that could be explored in future studies. Social exchange theory, for example, highlights the role of reciprocity and affection in shaping caregivers’ and recipients’ experiences, (Call et al., 1999; Ejem et al., 2018; Silverstein et al., 2002) while feminist and critical theory-driven analyses incorporate the sociopolitical structures that preference unpaid family-based caregiving (Barusch, 1995; Ward-Griffin & Marshall, 2003). Such policies can shape the size and composition of older adults’ networks, as countries with more limited social services have higher rates of family-centric networks (Djundeva et al., 2019). Although the economic strain on unpaid caregivers has received considerable attention,(Mudrazija, 2019; National Academies of Sciences, 2016) efforts to ameliorate financial burdens such as the Credit for Caring Act of 2021 define caregivers as family (including siblings and children of siblings) or members of household, which may affect non-family caregivers’ choices about for whom they will provide help. Such rules would have a disproportionate effect on adults aging solo, for whom half of help tasks are performed by non-family. The diversity of social roles engaged in caregiving for adults aging solo suggests opportunities for policies and programs that recognize and support caregivers beyond children and spouses.

While extensive research has been conducted on the stress, coping, and benefits for spouse and child caregivers of older adults,(Mehri et al., 2021; Moral-Fernández et al., 2018) far less is known about the challenges and needs of both caregivers and care recipients outside of close familial relationships, or factors that make exchange of help more likely (Wellman and Wortley 1990). An analysis comparing caregiving intensity and perceptions of burden among spouses, adult children, and extended/nonfamily caregivers found that the latter category experienced greater perception of isolation burden as the care recipient’s disability increased (Call et al., 1999). Subsequent qualitative research is needed to explore the nature of non-proximal caregiving relationships and strengths or challenges at the personal, interpersonal, health system or policy levels. We plan to conduct further analyses to assess clinical and demographic factors on care network size and function, and on longitudinal outcomes such as time to nursing home residence or death.

Conclusion

While lack of a spouse or children may place older adults at higher risk for isolation, this analysis suggests two important insights into how they receive help: First, adults without proximal family may cultivate a more diverse set of close relationships than those with spouses and nearby children, and secondly, those individuals can and do perform a high proportion of help-related tasks.

What this paper adds:

• Adults without spouses or children have more diverse social networks than married peers

• Friends, neighbors, siblings, and other family are primary sources of unpaid help for adults aging solo who receive help

• Focusing on unpaid caregiving for adults aging solo shifts research narrative from isolation to opportunities to build on social strengths

Applications of study findings:

• To improve equity, programs and policies to support unpaid help for older adults could be broadened to include non-family caregivers

• Future research could explore how adults aging solo and their caregivers offer and request help

Appendix 1: Supplemental Tables

Table A1.

Incidence and type of help received in past month

Received Help	Married-Children Nearby	Married-No Children	Single-Children Nearby	Aging Solo	Total	weighted p-value	F statistic F(3, 54)
Help with any independent activity of daily living	29%	17.5%	54.5%	54.6%	37.7%	<0.001	71.4
Rec’d help doing laundry last month	13.9%	9%	24.1%	28.7%	17.7%	<0.001	14.6
Rec’d help shopping last month	22.4%	12.9%	46.1%	37.2%	30.1%	<0.001	48.7
Rec’d help preparing meals last month	10.3%	6.1%	19.3%	20.8%	13.5%	<0.001	17.7
Rec’d help with banking last month	9.7%	4.5%	26%	20%	15.1%	<0.001	31.3
Help with any medical activities	86.7%	83.9%	78.1%	71.1%	82.7%	<0.001	9.2
Rec’d help taking medications last month	9.9%	5.2%	13.7%	21.4%	11.4%	<0.001	12.8
Attending medical visits	85.5%	83.4%	76.7%	64.7%	81.1%	<0.001	11.9
Help with any activity of daily living	34.6%	27.6%	43.5%	42.7%	37.3%	<0.001	8.8
Has help while eating	**	**	9.05%	10.41%	6.44%	0.001	16.4
Has help while bathing	9.3%	7.8%	16.4%	17.1%	12%	<0.001	12.0
Has help while toileting	**	**	3.55%	4.68%	3.28%	<0.001	6.2
Has help while dressing	24.4%	19%	19.2%	24.3%	22.3%	0.10	2.2
Received help getting around outside	13.6%	5.8%	29.6%	26.6%	18.8%	<0.001	35.7
Received help getting around inside	9.7%	4.7%	13.5%	13.6%	10.7%	<0.001	8.7
Received help getting out of bed	9.1%	5.7%	8.5%	8.6%	8.6%	0.40	1.0

A2:

Frequency of paid and unpaid help

Type of Care	Paid % (N)
	Married-Children Nearby	Married-No Children	Single-Children Nearby	Aging Solo	p-val (1&4)	p-val (2&4)	p-val (3&4)
Help with any IADLs	2.5%	4.2%	16%	32.8%	<0.01	<0.01	<0.01
Help with any medical activities	1.4%	**	7.6%	16.3%	<0.01	<0.01	<0.01
Help with any ADLs	1.6%	**	11.1%	21.5%	<0.01	<0.01	<0.01
Type of Care	Unpaid % (N)
	Married-Children Nearby	Married-No Children	Single-Children Nearby	Aging Solo	p-val (1&4)	p-val (2&4)	p-val (3&4)
Help with any IADLs	95.3%	96.6%	79.6%	66.9%	<0.01	<0.01	<0.01
Help with any medical activities	87.2%	86.4%	76.4%	65.6%	<0.01	<0.01	<0.01
Help with any ADLs	33.4%	27%	38.9%	30.2%	0.45	0.59	0.06

A3.

Sources of unpaid help, by group and task

Type of Care	Most frequent sources of unpaid help %
	Married-Children Nearby (raw N=1,278)	Married-No Children (raw N=247)	Single-Children Nearby (raw N=1,243)	Aging Solo (raw N=230)
Laundry	Spouse: 94%	**	Child: 76.2% Other family: 1.19%	Other family: 42.2% Other: 34.4%
Shopping	Spouse: 92.7%	**	Child: 83.7%	Other family: 45.4% Friend: 31.2%
Preparing meals	Spouse: 93.5%	**	Child: 85.8% Other family: 15.8%	Other family: 51.8% Other: 24%
Paying bills	Spouse: 93.2%	**	Child: 88.9% Other family: 8.2%	Other family: 52.5% Other: 14.8%
Help with any IADLs	Spouse: 96.6%	**	Child: 87%	Other family: 51.5%) Other: 26.2%
Managing medication	Spouse: 87.1%	**	Child: 87.2% Other family: 8.7%	Other family: 40.8% (20)
Medical appointment	Spouse: 91.1%	**	Child: 83.1% Other family: 10.8%	**
Help with any medical activities	Spouse: 91.9%	Spouse: 95.61%	Child: 83.4% Other family: 11.3%	**
Eating	**	**	**	**
Bathing	Spouse: 78%	**	Child: 68.5% Other family: 20.9%	**
Toileting	Spouse: 81.8%	**	**	**
Dressing	Spouse: 93.9%	**	Child: 74.5%	Other: 22.3%
Going outside	Spouse: 84%	**	Child: 82.6%	**
Walking inside	Spouse: 90.2%	**	Child: 83.4%	**
Getting out of bed	**	**	Child: 81.8%	**
Help with any ADLs	Spouse: 93 %	**	Child: 81.8%	**
Help with any activities	Spouse: 97.4%	Spouse: >95%	Child: 86.8%	Sibling: 32.6% Friend: 31.6% Other: 23.6% Niece/nephew: 15.5%

Spouse includes: Spouse, partner, boyfriend/girlfriend

Child includes: Child, child’s spouse, stepchild

Other family includes: sibling, grandchild, niece/nephew, other family

Other includes: renter/roommate, neighbor, clergy, ex-wife/ex-husband, other relative, other non-relative Totals may be >100% as some individuals reported multiple unique helpers for the same task.