Abstract
Objectives
Do adults without kin experience a care gap where they need help with activities of daily living but get no help from any source? We examine the prevalence of the care gap across Europe, and test whether those without partners or children substitute for their lack of close kin with help from broader networks, or whether they disproportionately experience care gaps.
Methods
Using data from the Survey on Health, Ageing and Retirement in Europe, we estimate the care gap in 28 European countries and Israel, how it varies, and who provides help for respondents with different family structures.
Results
The care gap is substantial, with 6.1% of all respondents ages 50 and above reporting a gap. It is highest in Western and Eastern Europe and lowest in Southern Europe and Israel. Respondents without partners or children are significantly more likely to have care gaps than those with close kin. However, respondents without close kin draw more often on more diverse networks of friends and relatives and use nursing home care.
Discussion
Our study introduces the concept of the care gap and shows that although it is most common among unpartnered adults without children it is also quite common for those with immediate family. A broader network partially but not completely substitutes for care gaps among those without immediate family. Our results offer new insights into the demand for public care services in countries with diverse welfare states.
Keywords: Caregiving, Europe, Family structure, Kinless
When confronted with difficulty with personal care and mobility, adults overwhelmingly turn to close family members, especially spouses, and children, for help (Janus & Koslowski, 2020; Mair et al., 2016; Patterson & Margolis, 2019). However, family structures around the world are shifting, and an increasing share of middle-aged and older adults are unpartnered and have fewer children than in the past (Verdery et al., 2019). When spouses, children, or other common caregivers are not available, such individuals may turn to more distantly related relatives, friends, neighbors, or paid or formal care (Allen et al., 2012; Barker, 2002; Fihel, et al., 2021). However, limited studies explore whether the rapidly growing population without close kin lacks the help they need as they encounter personal care and mobility challenges, or whether their needs are met by others.
Individuals experience a care gap when they report difficulty with activities of daily living (ADL) but receive no family or other unpaid care, no paid home care, and no nursing home care from any person. At the population level, it is useful to quantify the prevalence of the care gap experienced in different contexts, such as countries, because variation on this metric can help with health service provision and planning and because cross-national contextualization can reveal how care gaps vary across different macro-social environments. The need for care at the population level is shaped by population health and the size of the population requiring care, family structure affecting kin availability, and caregiving norms that shape whether needs are met and by whom. In the European context, all of these factors vary widely. The prevalence of reporting difficulty with personal care and mobility is highest in Southern Europe and lowest in Northern Europe (Ahrenfeldt et al., 2018). Family structure also varies, where 10% of adults 50 and older in Ireland, the Netherlands, and Switzerland have neither a spouse nor biological children, while only 3% lack these types of close kin in Czechia and Portugal (Verdery et al., 2019). Last, cultural norms and welfare state institutions related to caregiving differ widely across European countries, with some emphasizing family support (Daatland et al., 2011) and others nonfamily paid care (Deindl & Brandt, 2017; Haberkern & Szydlik, 2010).
In this article, we examine the care gap among middle-aged and older adults in Europe and Israel. We examine how the care gap varies at the individual level by family structure and at the population level by region. We test whether those without partners or children substitute for their lack of close kin with help from broader networks, or whether they disproportionately experience care gaps.
Measuring the Care Gap
The most cited analyses of a potential crisis of caregivers note the decline in the ratio of adults aged 45–64 (potential caregivers) to adults aged 80 and above (those disproportionately requiring care; Redfoot et al., 2013). However, examining care dynamics is complex, and requires a deep understanding of demographic and social changes that affect the availability and willingness of family and other network members to provide care to those in need (Freedman et al. 2023). Freedman and colleagues (2023) highlight the importance of examining the availability of family members who could provide care, as well as the micro level network of individuals, and the ways gaps may be filled differently across social groups and contexts.
A canonical distinction in the caregiving literature is that between formal and informal caregiving (Cantor, 1991; Litwak, 1985; Solé-Auró & Crimmins, 2014), with the former being help provided by family, friends, and other unpaid assistants and the latter being contracted help, either in-home or in nursing homes or similar facilities (Stall et al., 2019). Many studies emphasize that spousal caregiving remains the most common care arrangement (Bertogg & Strauss, 2020), highlighting that unpaid caregiving from family members remains dominant. However, research notes that some older adults lack close family members, which leads those who need help with personal care and mobility to rely on paid care or other arrangements (Deindl & Brandt, 2017; Mair, Quiñones, & Pasha, 2016). In addition to individual-level factors, other studies focus on country-level factors that predict older adults’ care arrangements, with higher levels of available paid care in Northern Europe and strong norms of family obligation to provide family care in Southern Europe (Saraceno & Keck, 2010; Suanet et al., 2012; Verbakel et al., 2017).
Existing research has not addressed the amount of care that is needed but not received in different contexts. Some studies contrast those who receive care and those who do not (Suanet et al., 2012), but such work tends to ignore a crucial difference among those not receiving care, blurring the distinction between need and access. More precisely, they conflate: (1) those who report no difficulty with personal care and mobility and do not receive care, and (2) those who do report difficulties with personal care and mobility and do not receive care (Floridi et al., 2021). We are aware of only one study that specifically tackles the issue of a gap in care in a related way. Pickard (2015) defines the “unpaid care gap” as a gap between the availability of care providers and the amount of care needed to meet care demands, finding that the unpaid care gap in England will likely increase over the next 15 years (Pickard, 2015). However, Pickard (2015) focuses only on the gap in unpaid care, ignoring paid care that may substitute or fill in gaps in caregiving.
Scholars also have discussed “unmet need,” focusing on the adverse consequences of not having care needs met (Beach & Schulz, 2017; Freedman & Spillman, 2014; Patterson et al., 2022). However, the conventional measures of unmet needs paint an overly conservative and incomplete picture of care needs, even after setting aside potential complications from the self-reported nature of unmet need measures (i.e., there is variation in willingness to report experiencing problems owing to a lack of care). Many people may find certain tasks difficult and need help they do not receive. This may increase the time needed to complete basic household tasks and generate daily stressors that are linked to poor health and well-being (Almeida et al., 2005), even if the lack of help has not led to negative consequences such as skipping meals or soiling oneself. In addition, many surveys do not include a measure of the negative consequences of not having care, limiting our ability to understand cross-national caregiving dynamics. Our conception of the care gap facilitates population-level estimation of those who receive no care for ADLs. Therefore, for both theoretical and practical reasons, we propose a new measure, defining the “care gap” as a lack of care despite difficulty with personal care and mobility.
Family Structure and Caregiving Arrangements
Family structure is an important predictor of care arrangements because family structure reflects the availability of potential caregivers in older adults’ social networks. Across diverse countries, there is consistent evidence that close family members provide the majority of care to older adults who need help with personal care and mobility (Broese van Groenou & De Boer, 2016). However, the increasing number of older adults without close kin (partners, children) worldwide (Freedman & Wolff, 2020; Verdery et al., 2019) may need to seek other care arrangements.
Classic gerontological theory suggests that when close kin is unavailable, other social ties may substitute for the roles traditionally played by children or partners (Cantor, 1979); however, the extent to which substitution is full or partial is unknown. Research finds that people with weak family networks may receive personal care support from extended family, nonfamily members, or paid care (Albertini & Pavolini, 2017; Fihel et al., 2021; Geerts & Van den Bosch, 2012; Lowers et al., 2023). Those lacking kin also report having more friends (Djundeva et al., 2019; Mair, 2019) and spending more time with friends (Margolis et al., 2022) than those with large family networks. However, it is unclear whether adults without close kin are more likely to experience care gaps, or whether substitution fills these gaps (Jacobs et al., 2018). We examine who provides care by family structure across a range of countries and investigate the extent to which nonfamily members fill the gaps left by thinning kinship networks.
Regional Differences in Caregiving Arrangements
Care arrangements vary widely from country to country (Fihel et al., 2021). Prior work suggests this variation is patterned by cultural norms and institutions (Haberkern & Szydlik, 2010; Suanet et al., 2012). For instance, in Southern and Central Europe, care is largely viewed as a family obligation, with legal requirements for children to support parents, and therefore family-based care may be more predominant (Daatland et al., 2011; Haberkern & Szydlik, 2010; Saraceno & Keck, 2010). Likewise, older adults in countries with higher levels of public health spending (e.g., the Netherlands and Denmark) are more likely to prefer government-based options to family-based care (Janus & Koslowski, 2020; Mair et al., 2016).
Cross-national differences in caregiving arrangements suggest that older adults in need of care who do not have available family members may fare better in certain contexts than others. For example, we might expect that in places like Northern Europe, which has higher levels of paid care, those without close family members will have a smaller care gap because they can more readily substitute formal for informal care (Deindl & Brandt, 2017; Floridi et al., 2021). In Southern and Eastern Europe, where dependence on family networks is predominant (Daatland et al., 2011), the care gap for older adults without close family members may be larger, particularly for countries with lower levels of formal care services (Quashie et al., 2022).
The Present Study
This article provides empirical evidence of the extent and nature of care gaps for older adults by family structure and variation across Europe. We address three research questions. First, we examine country- and region-specific variation in the prevalence of the care gap among middle-aged and older adults in the Survey of Health, Aging, and Retirement in Europe. Second, we examine how the individual care gap varies by family structure. We assess the extent to which middle-aged and older adults without a partner or children are more likely to report a care gap than those with such kin and how this varies by context. Third, we analyze who provides care for middle-aged and older adults who have difficulty with ADLs and ask whether those without available immediate family are distinctly disadvantaged in terms of the care gap or whether they receive either unpaid or paid help from others. Across all three research questions, we use a cross-national comparative framework, comparing our results by region in Europe to begin to uncover contextual variation in care gaps.
Data
The Survey of Health, Ageing, and Retirement in Europe (SHARE) is a cross-national longitudinal household survey of individuals over age 50 and their partners in 28 European countries and Israel (Börsch-Supan et al., 2013). SHARE is uniquely suited for this analysis because it provides high-quality data on health, caregiving, family structure, and sociodemographic factors, collected across many countries using harmonized questionnaires and coding schemes. To maximize the sample size and countries included in the study, we pool data from the 28 countries participating in Waves 6 and 8 (2015 and 2019)—the only waves that include consistent respondent-level questions about receipt of family and other unpaid care. Because we focus on understanding prevalence, rather than change, we treat our analysis as cross-sectional but adjust for clustering at the respondent level and retain all participants in either wave. We use the Harmonized SHARE Version F (https://g2aging.org/).
Our pooled sample from waves 6 and 8 includes 112,963 person waves based on 81,540 respondents aged 50 and older at the time of survey living in the community and nursing homes. We excluded 2 percent of the potential observations due to missing data on activities of daily living, receipt of help, and demographic and socioeconomic characteristics. Of the full analytic sample, 31,423 respondents (62,846 person waves) were in both waves 6 and 8, and 50,117 were in only one wave (either wave 6 or 8). After examining the full analytic sample (Tables 1 and 2), the second part of our analysis (Tables 3 and 5) focuses on the 12% of respondents who reported difficulty due to physical, mental, emotional, or memory problems with at least one of six ADLs (dressing, walking across the room, bathing/showering, eating, getting in or out of bed, using the toilet) or who live in a nursing home, and their caregiving arrangements.
Table 1.
Weighted Sample Characteristics by Caregiving Arrangements, Survey of Health, Aging and Retirement in Europe (Pooled 2015 and 2019 Samples)
| Disability status | Reports difficulty with activities of daily living | No difficulty with ADLs | ||||
|---|---|---|---|---|---|---|
| Caregiving arrangements | Care gap: Neither family/unpaid care nor paid care |
Only family/ unpaid care | Only paid care | Both family/unpaid and paid care | Live in nursing home | No care needed |
| Family characteristics | ||||||
| Family structure | ||||||
| Has partner and child(ren) | 50.7a,b,c,d | 56.0 | 22.4 | 44.8 | 15.4 | 66.0 |
| Has partner, no child(ren) | 3.7a,b,d | 4.5 | 3.9 | 3.8 | 0.9 | 4.3 |
| No partner, has child(ren) | 37.6a,b,c,d | 34.6 | 58.9 | 44.0 | 56.9 | 22.8 |
| No partner, no children | 8.0a,b,c,d | 5.0 | 14.8 | 7.4 | 26.8 | 6.9 |
| Demographic characteristics | ||||||
| Gender | ||||||
| Women | 58.3a,b,c,d | 57.1 | 71.2 | 65.5 | 66.6 | 53.1 |
| Men | 41.8a,b,c,d | 42.9 | 28.8 | 34.5 | 33.4 | 46.9 |
| Age | ||||||
| 50–54 | 5.5a,b,c,d | 3.7 | 0.6 | 1.2 | 0.3 | 10.7 |
| 55–59 | 17.6 a,b,c,d | 13.2 | 4.1 | 4.9 | 9.0 | 26.3 |
| 60–64 | 10.7a,b,c,d | 7.3 | 3.3 | 4.9 | 3.8 | 16.9 |
| 65–69 | 13.3 a,b,c,d | 9.0 | 4.8 | 5.8 | 5.0 | 14.6 |
| 70–74 | 12.8 a,b,c,d | 12.0 | 9.5 | 8.2 | 6.9 | 11.7 |
| 75–79 | 13.1a,b,c,d | 13.8 | 9.1 | 12.7 | 7.4 | 9.3 |
| 80+ | 27.1 a,b,c,d | 41.0 | 68.6 | 62.3 | 67.6 | 10.5 |
| Socioeconomic characteristics | ||||||
| Education | ||||||
| Less than upper secondary education | 45.2 a,b,c,d | 65.4 | 63.0 | 57.1 | 59.0 | 36.6 |
| Upper secondary and vocational training | 40.3 a,b,c,d | 27.1 | 28.4 | 32.3 | 26.8 | 41.4 |
| Tertiary education | 14.5 a,b,c,d | 7.5 | 8.7 | 10.6 | 14.2 | 22.1 |
| Total wealth (Euros) | ||||||
| ≤49,999 | 37.5 a,b,c,d | 40.9 | 43.0 | 42.3 | 75.7 | 25.3 |
| 50k–149,999 | 22.1 a,b,c,d | 29.5 | 21.5 | 20.7 | 11.3 | 21.8 |
| 150k–500k | 32.1a,b,c,d | 22.9 | 30.7 | 29.4 | 9.7 | 38.8 |
| ≥500k | 8.3a,b,c,d | 6.8 | 4.8 | 7.5 | 3.4 | 14.1 |
| Mean (SD)#ADL difficulty | 1.72 (0.06)a,b,c,d | 2.65 (0.07) | 2.61 (0.08) | 3.49 (0.07) | 2.44 (0.15) | NA |
| Region | ||||||
| Northern Europe | 4.9 a,b,c,d | 2.7 | 5.6 | 1.7 | 5.6 | 5.4 |
| Western Europe | 52.3a,b,c,d | 27.8 | 58.1 | 57.6 | 63.4 | 45.4 |
| Southern Europe | 22.6 a,b,c,d | 43.0 | 27.9 | 30.3 | 22.5 | 32.4 |
| Eastern Europe | 19.6 a,b,c,d | 25.7 | 4.6 | 8.1 | 7.2 | 15.4 |
| Israel | 0.7 a,b,c,d | 0.8 | 3.8 | 2.3 | 1.3 | 1.3 |
| Sample size (%) |
6,886
(6.1) |
3,796
(3.1) |
959
(0.9) |
1,536
(1.5) |
1,178
(0.9) |
98,608 (87.5) |
Notes: The analytic sample is all respondents aged 50 and older. The total N = 112,963.
We tested whether respondents with a care gap differ significantly from the following groups:
arespondents with only family/unpaid care
bthose who received only paid care
cthose who received both family/unpaid and paid care, and
dthose living in nursing homes (p < .05).
Table 2.
Disability and Caregiving Arrangements by Family Structure and Region, Survey of Health, Aging and Retirement in Europe (2015 and 2019)
| Disability status | Reports difficulty with activities of daily living | No difficulty with Activities of Daily Living |
Total |
||||
|---|---|---|---|---|---|---|---|
| Caregiving arrangements | Care gap: Neither family/unpaid care nor paid care | Only family/unpaid care | Only paid care | Both family/unpaid and paid care |
Lives in nursing home | No care needed | |
| Family structure | |||||||
| Has partner and child(ren) | 4.9a,b,c,d | 2.7 | 0.3 | 1.0 | 0.2 | 90.9 | 77,797 100% |
| Has partner, no child(ren) | 5.4 a,b,c,d | 3.2 | 0.8 | 1.3 | 0.2 | 89.1 | 4,669 100% |
| No partner, has child(ren) | 9.2 a,b,c,d | 4.2 | 2.1 | 2.6 | 2.1 | 79.8 | 24,945 100% |
| No partner, no children | 6.9 a,b,c,d | 2.1 | 1.8 | 1.5 | 3.5 | 84.2 | 5,552 100% |
| Region | |||||||
| Northern Europe | 5.8 a,b,c,d | 1.6 | 0.9 | 0.5 | 1.0 | 90.3 | 23,900 100% |
| Western Europe | 7.0 a,b,c,d | 1.9 | 1.1 | 1.9 | 1.3 | 86.9 | 35,050 100% |
| Southern Europe | 4.3 a,b,c,d | 4.1 | 0.8 | 1.4 | 0.6 | 88.8 | 35,875 100% |
| Eastern Europe | 7.6 a,b,c,d | 5.0 | 0.3 | 0.8 | 0.4 | 85.9 | 15,232 100% |
| Israel | 3.0 a,b,c,d | 1.9 | 2.5 | 2.6 | 0.9 | 89.0 | 2,906 100% |
| Total | 6,886 | 3,796 | 959 | 1,536 | 1,178 | 98,608 | 112,963 100% |
| 6.1% | 3.1% | 0.9% | 1.5% | 0.9% | 87.5% | ||
Notes: Sample weighted using person-level weights. Results by country are shown in Supplementary Table 1. The analytic sample is all respondents aged 50 and older. The total N = 112,963.
We tested whether respondents with a care gap differ significantly by region and family structure from the following groups:
arespondents with only family/unpaid care
bthose who received only paid care
cthose who received both family/unpaid and paid care, and
dthose living in nursing homes (p < .05).
Table 3.
Relative Risk Ratios from Multinomial Logistic Regression Model Predicting Caregiving Arrangements Among Respondents Who Report Difficulty with ADLs or Live in a Nursing Home, Survey of Aging, Health and Retirement in Europe (Pooled 2015 and 2019 Samples)
| Care Gap: Neither family/unpaid care nor paid care | Only paid care | Both family/unpaid and paid care | Live in nursing home | |
|---|---|---|---|---|
| vs only family/ unpaid care | vs Only family/ unpaid care | vs Only family/ unpaid care | vs Only family/ unpaid care | |
| Family structure (partnered, has children) | ||||
| Partnered, no child(ren) | 0.81 | 2.17* | 1.07 | 0.74 |
| Unpartnered, has child(ren) | 1.72*** | 3.44*** | 1.24 | 4.21*** |
| Unpartnered, no children | 2.32*** | 7.50*** | 1.79* | 17.87*** |
| Men (Women) | 0.87 | 0.85 | 0.79* | 1.11 |
| Age (50–54) | ||||
| 55–59 | 0.96 | 1.68 | 1.08 | 7.51** |
| 60–64 | 1.05 | 2.96 | 2.45 | 6.82** |
| 65–69 | 1.10 | 3.36* | 2.43 | 7.48** |
| 70–74 | 0.75 | 4.31** | 2.20 | 6.91** |
| 75–79 | 0.77 | 3.87* | 3.17* | 7.53** |
| 80+ | 0.55* | 8.33*** | 4.93** | 20.66*** |
| Education (Less than upper secondary education) | ||||
| Upper secondary and vocational training | 1.36** | 1.09 | 1.39* | 0.98 |
| Tertiary education | 1.64*** | 0.99 | 1.41 | 1.90** |
| Total wealth (≤49,999, Euros) | ||||
| 50k–149,999 | 1.05 | 0.80 | 0.70* | 0.24*** |
| 150k–500k | 1.57*** | 1.08 | 0.89 | 0.20*** |
| ≥500k | 1.17 | 0.50** | 0.67 | 0.18*** |
| Number of difficulties with ADLs | 0.72*** | 0.999 | 1.28*** | 0.96 |
| Regions (Western Europe) | ||||
| Northern Europe | 0.99 | 1.09 | 0.31*** | 0.93 |
| Southern Europe | 0.40*** | 0.25*** | 0.28*** | 0.23*** |
| Eastern Europe | 0.50*** | 0.07*** | 0.12*** | 0.08*** |
| Israel | 0.49** | 2.63*** | 1.18 | 1.01 |
| Constant | 5.11*** | 0.06*** | 0.16*** | 0.04*** |
Notes: The analytic sample is respondents aged 50 and older who have difficulty with at least one ADL or live in a nursing home. The total N = 14,355.
*p < .05; ** p < .01; *** p < .001.
Table 5.
Sources of Help by Family Structure and Region, Among Respondents Reporting Difficulty with ADLs and Living in Nursing Homes, SHARE (2015 and 2019)
| Family structure | ||||
|---|---|---|---|---|
| Partnered, has child(ren) | Partnered, no children | Unpartnered, has children | Kinless: Unpartnered, no children |
|
| Northern Europe | ||||
| Spouse/partner only | 18.5 | 15.3d | NA | NA |
| Children only | 2.1 | NA | 6.2e | NA |
| Mix of family members | 1.0 | 1.8 | 2.0 | 5.4 a,b,c |
| Nonfamily members only | 5.8 | 4.5 | 19.0 | 19.7a,b,c |
| Mix of family and nonfamily | 4.9 | 8.5 | 2.7 | 3.0 a,b |
| Live in nursing home | 4.7 | 7.6 | 14.2 | 21.9a,b,c |
| Care gap: receives no unpaid or paid care | 63.0 | 62.4 | 55.8 | 50.0a,b,c |
| Western Europe | ||||
| Spouse/partner only | 18.9 | 13.1d | NA | NA |
| Children only | 0.8 | NA | 5.5e | NA |
| Mix of family members | 0.9 | 0.0 | 1.3 | 4.0a,c |
| Nonfamily members only | 4.9 | 10.8 | 18.7 | 18.5a,b,c |
| Mix of family and nonfamily | 13.4 | 9.9 | 12.0 | 6.5a,b,c |
| Live in nursing home | 3.0 | 1.9 | 14.8 | 23.4a,b,c |
| Care gap: receives no unpaid or paid care | 58.1 | 64.3 | 47.7 | 47.7a,b |
| Southern Europe | ||||
| Spouse/partner only | 24.3 | 45.4d | NA | NA |
| Children only | 7.9 | NA | 29.9e | NA |
| Mix of family members | 6.1 | 8.5 | 2.4 | 16.8a,b,c |
| Nonfamily members only | 6.6 | 13.7 | 12.1 | 21.9a,b,c |
| Mix of family and nonfamily | 10.9 | 10.6 | 12.0 | 7.1a,b,c |
| Live in nursing home | 1.5 | 0.01 | 6.7 | 22.8a,b,c |
| Care gap: receives no unpaid or paid care | 42.7 | 21.9 | 36.9 | 31.5a,b,c |
| Eastern Europe | ||||
| Spouse/partner only | 24.6 | 30.7d | NA | NA |
| Children only | 5.6 | NA | 29.7e | NA |
| Mix of family members | 6.6 | 0.0 | 3.4 | 19.6 a,c |
| Nonfamily members only | 1.4 | 6.5 | 4.2 | 7.5a,b,cc |
| Mix of family and nonfamily | 4.8 | 21.1 | 6.4 | 6.7a,b |
| Live in nursing home | 1.0 | 5.2 | 3.3 | 12.5a,b,c |
| Care gap: receives no unpaid or paid care | 56.0 | 36.5 | 53.0 | 53.8a,b,c |
| Israel | ||||
| Spouse/partner only | 17.9 | 7.2d | NA | NA |
| Children only | 6.1 | NA | 8.0e | NA |
| Mix of family members | 1.2 | 0.0 | 0.0 | 5.0a |
| Nonfamily members only | 19.9 | 54.2 | 38.4 | 50.1a,b,c |
| Mix of family and nonfamily | 20.8 | 30.2 | 16.6 | 5.4a,b,c |
| Live in nursing home | 3.4 | 0.0 | 12.9e | 0.0 |
| Care gap: receives no unpaid or paid care | 30.7 | 8.4 | 24.1 | 39.4a,b,c |
Notes: The analytic sample is respondents aged 50 and older who have difficulty with at least one ADL or live in a nursing home. The total N = 14,355.
We tested whether kinless respondents differ significantly from respondents
awith a partner and children
bwith a partner and no children
cno partner and children
dWe also tested differences between those with a partner and no children from those with a partner and children, and
edifferences between no partner and children from those with a partner and children (p < .05).
Dependent variables
We analyze two outcomes. First, we construct a categorical variable combining ADL difficulties and caregiving arrangements. This measure classifies people as: (1) having no ADL difficulties and not living in a nursing home (no care needed), or having one or more ADL difficulties and either experiencing or receiving (2) a care gap, measured as no receipt of family/other unpaid, no paid home care in the last year, and not living in a nursing home, (3) only family/other unpaid care which includes help from any family member, friend or neighbor, (4) only paid home care, (5) both family/other unpaid care and paid home care, or (6) nursing home resident care.
Our second outcome is restricted to only respondents with at least one ADL difficulty and examines who provided help with activities of daily living in the last year. Based on data on all sources of help with ADLs, we construct a categorical variable for care recipients that classifies who provides care: (1) spouse/partner only, (2) children only, (3) mix of family members, (4) nonfamily members, (5) mix of family and nonfamily, (6) nursing home care, and (7) a care gap (neither family/other unpaid care nor paid home care).
Independent variables
Our key independent variable captures respondents’ family structure. We examine those with: (1) spouse/partner and child(ren), (2) spouse/partner but no child(ren), (3) child(ren) but no spouse/partner, (4) no spouse/partner or child(ren), the last of which we consider “kinless.” All living natural, foster, adopted, and stepchildren of respondents and/or respondents’ partner are included in our definition of children.
We group countries into five regions classified by the United Nations (United Nations, 1999): Northern Europe (Denmark, Estonia, Finland, Latvia, Lithuania, and Sweden), Western Europe (Austria, Belgium, France, Germany, Luxembourg, Netherlands, and Switzerland), Southern Europe (Croatia, Cyprus, Greece, Italy, Malta, Portugal, Slovenia, and Spain), Eastern Europe (Bulgaria, Czech Republic, Hungary, Poland, Romania, and Slovakia), and we show Israel as its own region.
We include demographic controls for gender and age (5-year age groups), and socioeconomic controls for education and wealth, as these factors shape individuals’ ability to take advantage of policies and paid caregiving and are associated with family caregiving norms (Bertogg & Strauss, 2020; Quashie et al., 2022; Van Groenou et al., 2006). Educational attainment is a three-tier harmonized scale designed to provide comparable education measures across countries (ISCED-97; OECD, 1999), including less than upper secondary education, upper secondary and vocational training, and tertiary education. Total wealth in Euros is coded into five groups: under or equal to €49,999, €50k to €149,999, €150k to €500k, and €500k and more. Finally, we control for a continuous measure of the number of difficulties with ADLs.
Method
First, we show descriptive characteristics of the pooled analytic sample (Table 1) that includes all respondents aged 50 and older. Next, we examine how the care gap and caregiving arrangements vary by family structure and region among all respondents aged 50 and older (Table 2). We also present the proportions of the care gap and caregiving arrangements by regions and countries in Supplementary Table 1. Then, we estimate a multinomial logistic regression model to predict caregiving arrangements by family structure and controls using the pooled sample limited to respondents that have difficulty with one or more ADL or live in a nursing home (Table 3). This part of our analysis assesses the extent to which middle-aged and older adults without a partner or children are more likely to report a care gap than those with such kin and how this varies by context. Last, we analyze who provides care for middle-aged and older adults who have difficulty with ADLs and ask whether those without available immediate family receive care (unpaid or paid) from other sources or if they are distinctly disadvantaged in terms of care (Tables 4 and 5).
Table 4.
Sources of Who Help by Family Structure, Among Respondents Reporting Difficulty with ADLs or Living in Nursing Homes, SHARE (2015 and 2019)
| Family structure | ||||
|---|---|---|---|---|
| Partnered, has child(ren) | Partnered, no children | Unpartnered, has children | Kinless: Unpartnered, no children | |
| Sources of Who Help | ||||
| Spouse/partner only | 21.4 | 24.2d | NA | NA |
| Children only | 3.8 | NA | 17.4e | NA |
| Mix of family members | 3.4 | 2.6 | 2.1 | 10.3a,b,c |
| Nonfamily members only | 4.9 | 11.3 | 14.2 | 18.1a,b,c |
| Mix of family and nonfamily | 10.9 | 11.1 | 10.6 | 6.6a,b,c |
| Live in nursing home | 2.3 | 1.8 | 10.1 | 21.4a,b,c |
| Care gap: receives no family/unpaid, or paid care | 53.3 | 49.0 | 45.6 c | 43.5a,b,c |
| Total | 100 | 100 | 100 | 100 |
Notes: The analytic sample is respondents aged 50 and older who have difficulty with at least one ADL or live in nursing home. The total N = 14,355.
We tested whether kinless respondents differ significantly from respondents
awith a partner and children
bwith a partner and no children
c no partner and children
dWe also tested differences between those with a partner and no children from those with a partner and children and
edifferences between no partner and children from those with a partner and children (p < .05).
Furthermore, we conduct sensitive analyses to examine how the care gap and caregiving arrangements vary by age, separating the sample into two age groups: 50–69 and 70 and older. We present the proportions of the care gap and caregiving arrangements by age in Supplementary Table 2. Then, we examine a multinomial logistic regression model to predict caregiving arrangements by family structure for each age group (Supplementary Tables 3). Finally, we explore who provides care by age group in Supplementary Table 4.
All analyses use SHARE-provided person-level weights and robust standard errors to account for the survey design and the cluster sampling induced by some respondents contributing to two observations or living within the same household in our pooled sample.
Results
Sample Characteristics
Table 1 shows sample characteristics for the pooled sample, highlighting associations between caregiving arrangements and family, demographic, and socioeconomic characteristics. The column on the right indicates respondents who report no difficulty with ADLs (87.5% of the total sample). The other columns indicate the types of care respondents receive from different sources. Of the whole sample, 6.1% of middle-aged and older adults experience a care gap. These are respondents who report difficulty with ADLs but report no family/unpaid care or paid home care in the last year and are not living in a nursing home. Turning to the rest of the population, 3.1% rely only on family and other unpaid care, 1.5% rely on both unpaid care and paid home care, 0.9% rely only on paid home care, and 0.9% live in a nursing home.
Respondents who report a care gap are more likely to be male, be younger, have higher levels of education and wealth, and report difficulty with fewer ADLs than those with different caregiving arrangements. Those relying on family and other unpaid caregivers have lower levels of education and are more likely to be in Southern and Eastern Europe. Paid care (both alone and combined with family/unpaid care) is more common among the unpartnered, women, those over 80, and those with lower levels of education and wealth. Last, those living in nursing homes are the most likely to include kinless respondents (no partner or children) and have low levels of education and wealth.
Family Structure and Caregiving Arrangements Across Regions
Table 2 presents the care gap and other caregiving arrangements by family structure and region. All caregiving arrangements differ by family structure. Respondents with partners and children are the most likely to not need care (90.9%), compared with respondents with other family structures. Among this group, few respondents rely on paid home care (0.3%), a mix of family and paid care (1.0%), or live in a nursing home (0.2%). Instead, this group is more likely to rely on only family and other unpaid care (2.7%) and is least likely to have a care gap (4.9%). Those with a partner but no children (the second row) are almost as likely to not require help (89.1%), but 5.4% report a care gap, and some rely on family care (3.2%), paid care (0.8%), both family and paid care (1.3%) and are unlikely to rely on nursing home care (0.2%).
Those without a partner are more likely than the partnered to report difficulty with ADLs. Likewise, respondents without a partner report a higher care gap and higher reliance on paid care, a mix of unpaid and paid care, and nursing home care. For example, 6.9% of respondents without a partner or children (kinless) have a care gap, and 9.2% of those with children but no partner have a care gap. Additionally, kinless respondents have the highest rates of living in a nursing home.
Regionally, Eastern Europe has the highest care gap (7.6%), followed by Western Europe (7.0%), Northern Europe (5.8%), Southern Europe (4.3%), and Israel (3.0%). Northern Europe has the highest prevalence of respondents that no care needs (90.3%). The prevalence of relying on only family and other unpaid caregivers is variable across regions, but highest among the countries of Southern and Eastern Europe (4.1% and 5.0%, respectively).
Table 3 shows the relative risk ratios from the multinomial logistic regression model predicting caregiving arrangements. The reference group is respondents only receiving family and other unpaid care. In this part of the analysis, we focus on comparing kinless respondents (without a partner or children) to those with other family structures. We examine to what extent kinless respondents rely on different caregiving arrangements, net of their different socioeconomic and other characteristics.
Compared with receiving family and other unpaid care, respondents without a partner or children are significantly more likely to have care gaps than respondents who have a partner and children, net of all control variables (RRR 2.32). The kinless are also significantly more likely than respondents with a partner and children to rely only on paid care (RRR 7.50), rely on a mix of family/unpaid and paid care (RRR 1.79), or live in a nursing home (RRR 17.87). These results highlight the vastly different caregiving arrangements of those lacking close kin compared to those with partners and children. Additionally, we find those with children but without a partner are also more likely to have a care gap (RRR 1.72), and to rely on paid care (3.44) and nursing homes (RRR 4.21) compared to those with both a partner and children. However, the relative risk ratios for this group are much lower than those for the kinless. Statistical tests indicate that this group differs from the kinless, with kinless respondents significantly more likely to receive paid care or live in a nursing home.
Last, we present regional differences at the bottom of Table 3. Compared with Western Europe, respondents in Southern and Eastern Europe are less likely to have a care gap and less likely to receive only paid care, showing that these regions rely most on family and other unpaid caregiving. Respondents in Israel are more likely to rely on only paid home care and have a significantly lower care gap than respondents in Western Europe.
Family Structure and Sources of Care Across Regions
The last part of our analysis examines how sources of caregiving vary by family structure among the subsample of respondents who either report difficulty with activities of daily living or who live in nursing homes (Table 4). We explored who provides unpaid family care or paid care, including any family and nonfamily members; all columns exclude irrelevant cells (e.g., those without children cannot receive care from children) and add to 100%.
First, we test to what extent kinless respondents are disadvantaged in terms of caregiving, or alternatively, if they receive help from others in their network. Kinless respondents with no partner or children have a very different mix of people helping them than those with either a partner or children or both. Among the kinless, the first two categories are not applicable, because they do not have a partner or children. Rather than relying on these traditional sources of help, the kinless are significantly more likely to rely on a mix of family members (10.3%), nonfamily members only (18.1%), and nursing homes (21.4%). They are less likely than those with more kin to rely on a mix of family and nonfamily (6.6%). Because of this more varied mix of helpers, kinless respondents who require help actually have a lower care gap than those with more family members. We note that this pattern would look much different if we excluded nursing homes. This is an important point with substantial bearing on the literature: most prior analyses exclude nursing home respondents and do not examine nursing homes in the mix of caregiving.
Second, looking at respondents with other family structures, we see that unpartnered respondents with children rely much more on their children as a sole source of caregiving than those with a partner and children. They also have much higher nursing home use (10.1%) than those with a partner, a finding replicated from previous research (Geerts & Van den Bosch, 2012; Lowers et al., 2023).
Finally, Table 5 examines to what extent these patterns differ across regions, especially for kinless respondents. Across European regions, kinless respondents have the highest rates of living in nursing homes (21.9% in Northern Europe, 23.4% in Western Europe, 22.8% in Southern Europe, and 12.5% in Eastern Europe). In addition to relying on nursing homes for help, they also rely on nonfamily members more than those with immediate family. Kinless respondents in Southern and Eastern Europe tend to rely on a mix of extended family members, a pattern that is less evident in Northern and Western Europe and Israel. Summing up, kinless respondents rely on a mix of people to help when they have difficulty with the activities of daily living, and nursing home care constitutes a considerable portion of that care for the kinless across European regions.
Supplementary Analysis
Differences in life stage may be associated with the risk of experiencing a care gap. Thus, we conduct additional analyses by age group and present the results in Supplementary Tables 2–4. Our findings in Supplementary Table 2 indicate that the care gap is higher among respondents aged 70 and older (9.1%) than those aged 50–69 (4.5%). The multinomial logistic regression models in Supplementary Table 3 shows that among respondents aged 50–69, only unpartnered respondents with children are significantly more likely to have the care gap (RRR 1.84) than those who are partnered with children. However, among respondents aged 70 and older, the relative risk ratios for the care gap become significant for respondents without close kin (RRR 2.74). Finally, the results in Supplementary Table 4 show that respondents aged 50–69 are likely to receive care from spouse/partner only (14.6%). For respondents aged 70 and older, they are likely to receive care from diverse sources. Kinless respondents aged 50–69 are more likely to have a care gap (55.2%) and rely on a mix of family members (12.4%), while those aged 70 and older tend to receive care from nonfamily members (21.6%) or live in a nursing home (25.2%).
Discussion
As the twin forces of population aging and thinning family networks continue to collide around the world, many societies will face increased challenges in helping older adults receive care to meet their needs. However, whether adults without close kin lack help when needed, and whether they receive help from others in their broader networks is unknown. We explore whether care gaps vary across contexts and whether other sources of care, like extended social ties and nursing homes, fill caregiving needs.
Family Structure and Substitution for Care Gaps
In this study, we first examine the extent of care gaps across Europe, highlighting their high prevalence in all contexts, and providing the first empirical evidence of care gaps in the region. Our results indicate that 6.1% of adults aged 50 and above report difficulty with ADLs and report receiving no family care, no paid care, and do not live in nursing homes. There is some variation across Europe, with the highest care gap in Eastern Europe (7.6%), followed by Western Europe (7%), Northern Europe (5.8%), Southern Europe (4.3%), and Israel (3.0%). The difference across regions in the prevalence of gaps in care may be related to diverse cultural norms and welfare state institutions (Daatland et al., 2011), such as the acceptability and availability of paid care, nursing home use, and extended family support (Saraceno & Keck, 2010).
Second, we examine how the prevalence of care gaps varies by family structure. Our findings highlight clear patterning on this dimension. Our multivariate models show that kinless middle-aged and older adults have a much higher relative risk of having a care gap than those with either a partner or children. However, those without close kin also are more likely to receive paid care or live in a nursing home than those with a partner and children. This finding has important implications for policymakers and aging adults themselves, as they provide some window into the likely future of changing caregiving dynamics in the face of thinning family networks.
Third, we explore who provides care for adults aged 50 and older with ADLs and whether an extended network substitutes for partners or children. Our results are consistent with research showing that those with small family networks (e.g., kinless adults) receive some help from extended family or nonfamily members (Albertini & Pavolini, 2017; Deindl & Brandt, 2017; Fihel et al., 2021; Geerts & Van den Bosch, 2012; Lowers et al., 2023). Although there is some substitution occurring from a mix of family members, nonfamily members, or reliance on nursing homes, substitution does not fill care gaps of kinless adults. For all groups, even the kinless, extended family and nonfamily members constitute a small share of care providers. Other social ties may substitute for caregiving traditionally filled by children or partners (Djundeva et al., 2019; Mair, 2019), but they do not fully compensate (Jacobs et al., 2018).
Finally, our supplementary analyses show evidence of variation in care gaps across the life course. Overall, we find a higher care gap among respondents aged 70 and older than those aged 50–69. However, analyses limited to respondents with ADLs only, show that respondents aged 50–69 are more likely to experience a care gap than those aged 70 and older. Indeed, respondents aged 70 and older have more diverse sources of care than younger respondents. Different life course trajectories may affect sources of care. For example, although individuals in their 50s are less likely to be widowed than people in their 80s, they may be unpartnered due to divorce or a breakup of a cohabiting union, leading to a care gap or change in the sources of care (Carr & Utz, 2020). Our findings suggest that future research is needed to expand our understanding of heterogeneity in characteristics of the care gap and sources of care across middle age and older adulthood.
Regional Differences and Substitution for Care Gaps
In the final part of this study, we discuss regional differences in care arrangements. Some care substitution occurs across all European regions, and the mix of caregivers varies by region as well as family structure. Generally, most middle-aged and older adults rely on partners for help across regions (Bertogg & Strauss, 2020). However, those without a partner receive more help from nonfamily members in Northern and Western Europe, but in Southern and Eastern Europe they rely on help from children. Explanations for the regional differences in care arrangements may be related to the norms of familial caregiving and the availability of paid care (Haberkern & Szydlik, 2010). Our findings confirm that in countries thought to have more familistic norms, such as places in Southern and Eastern Europe, there is more care provided for older adults because of increases in extended family caregiving involvement (Daatland et al., 2011). In contrast, middle-aged and older adults without close kin are more likely to receive help from nonfamily members only or to live in a nursing home in Northern and Western Europe, with comparably little help from extended family members. A possible explanation for this pattern is that countries in Northern and Western Europe have stronger welfare states and public institutions and therefore have higher availability of paid care (Albertini & Pavolini, 2017; Geerts & Van den Bosch, 2012). Additionally, we find a difference in the care arrangements among people without close kin in Eastern and Southern Europe. Kinless middle-aged and older adults in Eastern Europe have the largest population-level care gaps among the regions we studied. If people are without close kin and paid care is also unavailable or inaccessible, care gaps may increase in the future. In Eastern Europe, the high proportion of kinless respondents experiencing a care gap may be related to a lack of sufficient paid care to partially substitute for care from close kin (Fihel et al., 2021; Quashie et al., 2022) even though they receive help from extended family members.
There are some limitations to this study. First, SHARE does not include data on the adverse impact of care gaps and lacks more details about care needs with ADLs, thus we cannot explicitly measure traditional conceptions of unmet need (Freedman & Spillman, 2014; Patterson et al., 2022), amount of care received, or different levels of care needs with ADLs. For example, we cannot capture respondents receiving help with some tasks but not others because the survey does not enumerate task-specific help. Moreover, SHARE also does not ask about assistive devices, which may also compensate for care needs. Future research may assess unmet need to examine adverse consequences of insufficient help or use other data sources with more detailed data, improving upon our estimates of the caregiving gap in a particular context.
Second, we are not able to assess more nuanced measures of care arrangements due to the small sample size for some countries in SHARE data, such as Israel. For example, we are not able to distinguish differences in caregiving from biological children versus stepchildren, or whether paid care is private or public. Similarly, we cannot disentangle drivers of family structure (e.g., are the “not partnered,” never married, divorcees, or widows), which may differ by life stage. These factors may affect older adults’ care arrangements. Future surveys with more countries and more observations would enable a better estimation of these detailed correlates of the care gap and caregiving more generally.
Third, our analysis does not capture dynamic changes in family structure, changes in disability, and caregiving receipt. For example, family structure changes (e.g., a spouse’s death) may be associated with changes or transitions in care arrangements. Another example is adults who divorced during midlife and experience a care gap may subsequently repartner and no longer experience a gap in care. Future research should measure dynamic patterns in care trajectories, examining variation across different points in the life course.
Despite limitations, our study showcases the importance of examining care gaps. Although many previous studies examine variation in caregiving arrangements, our study highlights 1) the high prevalence of care gaps, with many middle-aged and older adults reporting difficulty with daily tasks but not receiving any help, 2) the importance of kin availability and family structure for shaping care gap risk and the types of care relied upon, and 3) the ways in which older adults without close kin tend to rely on their broader networks and nursing home care to partially fill their care needs. As populations globally continue to age and family structures shift, different societies will have to grapple with meeting adults’ care needs. An increase in demand for care combined with changes in family structure means that there is a need for policies promoting and easing the financial burdens of paid care services and support for caregivers from a broad network of relatives and non-relatives. Policies of this nature may help to shrink the care gap and encourage nonfamily members to provide care, especially for older adults without close kin. Countries with weak welfare states will need to invest more in supporting alternatives to family-based care for those without available kin. There is great variation in how countries do this currently, and future research should continue to examine how care needs and solutions evolve over time.
Supplementary Material
Contributor Information
Huijing Wu, Department of Sociology, University of Western Ontario, London, Ontario, Canada.
Rachel Margolis, Department of Sociology, University of Western Ontario, London, Ontario, Canada.
Mara Getz Sheftel, Population Research Institute, Pennsylvania State University, University Park, Pennsylvania, USA.
Ashton M Verdery, Department of Sociology and Criminology, Pennsylvania State University, University Park, Pennsylvania, USA.
Funding
This work was supported by the Government of Canada—Canadian Institutes of Health Research (MYB-150262), Social Sciences and Humanities Research Council (435-2017-0618 and 890-2016-9000), National Institute on Aging (1R01AG060949), the NIA funded Changing Demography of Family Care Network (P30AG012846), Pennsylvania State University Population Research Institute (supported by an infrastructure grant by the Eunice Kennedy Shriver National Institute of Child Health and Human Development P2C-HD041025). The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH or other funding sources. The SHARE data collection has been funded by the European Commission, DG RTD through FP5 (QLK6-CT-2001-00360), FP6 (SHARE-I3: RII-CT-2006-062193, COMPARE: CIT5-CT-2005-028857, SHARELIFE: CIT4-CT-2006-028812), FP7 (SHARE-PREP: GA N°211909, SHARE-LEAP: GA N°227822, SHARE M4: GA N°261982, DASISH: GA N°283646) and Horizon 2020 (SHARE-DEV3: GA N°676536, SHARE-COHESION: GA N°870628, SERISS: GA N°654221, SSHOC: GA N°823782, SHARE-COVID19: GA N°101015924) and by DG Employment, Social Affairs & Inclusion through VS 2015/0195, VS 2016/0135, VS 2018/0285, VS 2019/0332, and VS 2020/0313. Additional funding from the German Ministry of Education and Research, the Max Planck Society for the Advancement of Science, the U.S. National Institute on Aging (U01_AG09740-13S2, P01_AG005842, P01_AG08291, P30_AG12815, R21_AG025169, Y1-AG-4553-01, IAG_BSR06-11, OGHA_04-064, HHSN271201300071C, RAG052527A) and from various national funding sources is gratefully acknowledged (see www.share-project.org). The development of the Harmonized SHARE was funded by the National Institute on Aging (R01 AG030153, RC2 AG036619, R03 AG043052).
Conflict of Interest
None.
Data Availability
This paper uses data from SHARE Waves 6 and 8 (DOIs: 10.6103/SHARE.w6.800, 10.6103/SHARE.w8.800, 10.6103/SHARE.w8ca.800), see Börsch-Supan et al. (2013) for methodological details (1). This analysis uses data or information from the Harmonized SHARE dataset and Codebook, Version F as of June 2022 developed by the Gateway to Global Aging Data. For more information, please refer to https://g2aging.org
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
This paper uses data from SHARE Waves 6 and 8 (DOIs: 10.6103/SHARE.w6.800, 10.6103/SHARE.w8.800, 10.6103/SHARE.w8ca.800), see Börsch-Supan et al. (2013) for methodological details (1). This analysis uses data or information from the Harmonized SHARE dataset and Codebook, Version F as of June 2022 developed by the Gateway to Global Aging Data. For more information, please refer to https://g2aging.org