Changes in the Provision of Family Care to Frail Older People in Familistic Welfare States: Lessons From Israel and Italy

Abstract

Objective: Our article aims to investigate changes in the rate of informal care provision, which occurred in Israel and Italy in the last decade. In addition, we analyze typology and magnitude of the main factors contributing to explain the probability of providing informal care. Method: We used data from the Survey of Health, Ageing and Retirement in Europe (SHARE) at two selected time points (2006/2007 and 2015). Results: The probability of offering social support to elder family members who live outside the household has been trending down substantially over the years. The likelihood of providing unpaid care is significantly higher when one performs volunteer or charitable work and/or engages in leisure activities, and the importance of these two variables has been growing over the years. Discussion: Israel and Italy have experienced over the years a remarkable decline in the share of older adults providing informal care. The article helps to identify which factors have been associated with this phenomenon.

Keywords

long-term care informal caregiver intensive care social support SHARE

Introduction

Family Caregivers as the Backbone of Long-Term Care (LTC) Provision in Aging Societies

Family care represents the main source of support for the increasing number of frail older people in our aging societies (Colombo & Frits, 2011; Muir, 2017; Naiditch, Triantafillou, Di Santo, Carretero, & Durrett, 2013). This is true even in countries with a well-developed LTC system—including under this term all home and residential care services as well as cash-for-care benefits—such as the Swedish welfare state (Johannson & Schön, 2017). This substantial support is provided by caregivers not only to older relatives who co-reside with them, but often also to those living outside of their own household (Center for Policy on Aging, 2014; Lamura et al., 2008). Data from the United States show that the majority of caregivers (66%-68%) provide help to older adults living in a different household than their own, this being true also for situations of intensive care (Schulz & Eden, 2016). Within Europe, informal care provision outside of one’s own household is more likely—while less intensive—in the Nordic countries (characterized by a lower number of multigenerational households), and less frequent in Eastern and Southern Europe (Rodrigues, Huber, & Lamura, 2012).

Family caregivers of older people are overrepresented among women, especially as spouses or middle-aged daughters (Lamura et al., 2008; Schulz & Eden, 2016), in older age groups, and among the better educated (Abramowska-Kmon, Kotowska, & Latkowski, 2015). While the majority seems to provide a limited amount of hours per week, for some of them—especially in Southern and Eastern Europe—informal care represents an intensive, time-consuming accomplishment, especially when delivered to co-residents (Albertini, 2016; Colombo & Frits, 2011; Verbakel, Tamlagsrønning, Winstone, Fjær, & Eikemo, 2017). Informal care has been often associated with a deterioration of the caregivers’ health, especially in the case of intensive and prolonged care, and particularly when recipients report dementia-related behavioral disturbances (Bauer & Sousa-Poza, 2015; Schoenmakers, Buntinx, & Delepeleire, 2010; Verbakel et al., 2017; Vlachantoni, Evandrou, Falkingham, & Robards, 2012). This impact seems to be stronger in the case of low-income or low-educated caregivers (the American Association of Retired Persons (AARP) and National Alliance for Caregiving, 2015).

Employment and material security (i.e., the overall ability to make ends meet) represent relevant features in caregiving-related phenomena, too. As for employment, informal caregivers are exposed to different consequences, depending upon the availability of LTC services, on one hand, and of work–life balance reconciliation measures, on the other hand. Thanks to a relatively widespread availability of both, in Northern Europe providing informal care does not lead usually to a significant reduction in employment, whereas the opposite is true in Southern Europe (European Commission, 2013), with the possible partial exception of Italy (Principi et al., 2014), where a relatively generous care leave model is in place (Schmidt, Fuchs, & Rodrigues, 2016). A systematic review of measures to support work–life balance across Europe (Bouget, Spasova, & Vanhercke, 2016) has shown that informal care might lead to income losses and a weaker position in the labor market, unless policy tools are put in place to prevent this risk, such as flexible working arrangements, care benefits, and allowances promoting informal caregivers’ employability and well-being. The availability of residential care opportunities, rather than of home care, can also have a positive effect on work attendance of care recipient’s children (Gautun & Bratt, 2016).

Cultural norms in affecting social behaviors have been also identified as factors potentially affecting the share of the population supporting older relatives, as a consequence of a different perception of family responsibilities in elder care provision (Katz, Lowenstein, Halperin, & Tur-Sinai, 2015). However, the direction of this influence is not univocal, as shown by the fact that some Western European countries, characterized by a lower propensity toward filial care responsibility (such as France and Norway), paradoxically report higher shares of adult children supporting their parents, when compared with Central and Eastern European countries (Dykstra, Kotowska, & Mari-Klose, 2016).

Among the theoretical attempts to consider the different dimensions mentioned above within a holistic approach aimed at explaining what might affect informal care provision, the recently developed “Informal Care Model” (Broese van Groenou & De Boer, 2016) considers a variety of both individual and contextual factors. These include, besides psychological attitudes and normative beliefs, also existing barriers (such as the distance between the recipient and provider of informal care, the time availability of the latter, as well as his or her resources and competences) and the role played by the family, the social network, and the community. While no research has already tested empirically the validity of this only recently developed framework, its comprehensiveness can be useful to systematize the large number of elements potentially affecting informal care and its elements have been considered in the methodological approach followed for this study.

Peculiarity of the Italian and Israeli Formal and Informal Care Contexts

Within the above described context, Italy and Israel share, to some extent, similar characteristics, but present at the same time some crucial differences in terms of formal and informal LTC provision (Casanova, Tur-Sinai, & Lamura, 2019). Among the most evident commonalities is the strong role of the family in providing LTC, as highlighted by the share of persons aged 50 years and older who care for someone living in the same household, which reaches in both countries a similar level of approximately 7%, that is, above the average of the 15-country sample reached by the fifth wave of the Survey of Health, Ageing and Retirement in Europe (SHARE; Wagner & Brandt, 2015). The peculiar role of informal care is confirmed by results emerging from an earlier wave, highlighting that in both Israel and Italy the intensity of informal care received (measured in number of hours per week) is among the highest, and co-residential informal care is relatively common (Rodrigues et al., 2012).

A second, related common feature of both systems is the widespread employment of migrant workers as a support to home-based care provision, often on a live-in basis. Estimates indicate that approximately 80% of Italy’s domestic care work is provided by migrants, and that these account for approximately 50% of Israel’s workforce in the home care sector (Luppi, Oomkens, Knijn, & Weicht, 2015). In Italy, home-based migrant care workers are mainly employed directly by households (which use primarily care allowances to this purpose, thus becoming de facto their employers). In Israel, instead, they are mostly hired through a mixed model, including, on one hand, private care-providing agencies (paid from the state in the form of care benefits) and, on the other hand, those families (representing the majority of recipients) who employ the migrant care worker for a larger number of hours than those allocated by the state care benefits (Shamir, 2013).

The two countries differentiate from each other, possibly to a larger extent, with regard to other LTC-related facets. A first difference concerns the much older age structure of the Italian population, reflecting a potentially higher level of LTC demand; whereas in Israel the above-65-year-old population reached 11.3% of the total in 2016, the Italian value at 22% was almost twice as high (Organisation for Economic Co-Operation and Development [OECD], 2018b). On the provision side, a major difference can be identified in the much larger coverage of LTC services existing in Israel, especially with regard to home care, which reaches 15% to 20% of the over-65-year-old population, versus less than 5% in Italy (Carrera, Pavolini, Ranci, & Sabbatini, 2013). As for informal care, the female employment rate is much higher in Israel than in Italy, thus theoretically contributing to facilitate informal care provision in the latter country as traditionally this is primarily provided by women in working age (OECD, 2018a).

Another major difference concerns the impact of the recent international economic recession (Foscolou et al., 2017). Italy has been one of the most affected nations and, together with Greece, the only European country with a negative gross domestic product (GDP) growth in the 2012 to 2017 period, whereas Israel has shown a much more limited impact (Almor, 2011; Brand, Weiss, & Zimring, 2017). Older population groups seem to have been better safeguarded from the recent crisis by the social protection systems, as reflected by the decreasing poverty rates recorded among people aged above 65 years in most European countries (Karpinska et al., 2016). Notwithstanding, longitudinal data seem to suggest that, in Italy, between 2004 and 2011 the group of people aged above 50 years reported the largest Europe-wide increase in the financial or practical support received from others (Ogg & Renaut, 2013). At the same time, however, between 2006 and 2013, the increase in intergenerational transfers of both practical and financial support from the older to the younger generations was lowest in Italy (Karpinska et al., 2016). This might be partly related to the fact that the constraints imposed by the crisis on public budgets and the following cuts on public services are likely to have caused a significant impact in cutting overall care provision. This in turn has, on one hand, posed a heavier burden on households and, on the other hand, pushed for private care solutions (e.g., via privately paid care workers) to face the increasing elder care needs (Picchi, 2016).

Focus of the Analysis Presented in this Article

In the light of the phenomena and dynamics highlighted above, this article will aim in the first place at investigating the changes in the rate of informal care provision that have occurred in Israel and Italy in the last decade. This will be achieved by comparing the developments that have occurred in the two countries with trends emerging in the wider international context. In a second step, we will analyze the typology and magnitude of the main factors contributing to explain the probability of providing informal care at the two selected time points. These will include basic sociodemographic variables, health-related aspects, socioeconomic status, as well as provided and received social and financial support. Finally, we will discuss the policy implications emerging from the illustrated results, and formulate some concluding recommendations.

Measures and Methods

Data Source and Study Sample

This study is based on the SHARE, a multidisciplinary and cross-national longitudinal survey of persons aged 50 years and older (Achdut, Tur-Sinai, & Troitsky, 2015). The micro data collected by SHARE allow us to compare the dynamics of health, economic situation, and welfare of older people in different European countries over time (Katz et al., 2015), thus providing a valuable support for evidence-based policy making to address population aging-related challenges (Börsch-Supan et al., 2013). Altogether, 8,000 and 3,668 persons aged 50+ years from Italy and Israel, respectively, were included in the study. To our knowledge, SHARE is the only survey that provides comparable information over a longer period of time on informal care patterns as the last wave of the European Quality of Life Survey (also containing items on this topic) is not fully comparable to previous waves (see the section “Data analysis” here: https://statswiki.unece.org/display/AAI/Annex+A.2%3A++Information+on+AAI+indicators+for+the+second+domain%3A+Participation+in+Society).

The specific data analyzed for the study reported in this article refer to persons examined in two of the countries included in SHARE—Italy and Israel—by drawing on two research “waves” of SHARE. With regard to Italy, the study uses data gathered in the first year of Wave II (2007: hereinafter: Time 1), and those from the most recent wave, the sixth (gathered in 2015, hereinafter: Time 2). As for Israel, the study uses data collected in the second year of Wave I (2006: hereinafter: Time 1), and those from the most recent wave, the sixth (collected in 2015, hereinafter: Time 2). This approach allows to place the research periods for each of the investigated countries at 8 or 9 years apart, thus enough time to allow testing and estimation of changes in both the explained variable and in the array of factors potentially predicting the changes in its values over time.

Research Variables

Explained variable

In each of the waves of SHARE, respondents are asked a series of questions that concern the “social support” that they gave to older people outside their household in the 12 months preceding the interview. The choice of these questions was driven by the fact that, while SHARE includes variables capturing the provision of care and/or support to people living both in the same household and outside of the caregiver’s household, in Italy and Israel the latter situation represents the overwhelming majority of situations (i.e., over 78% and over 88% of cases, respectively, in the last wave). Therefore, to be able to provide more unambiguous and societally more relevant results, we opted for considering only this form of caregiving.

Social support is defined as providing any of the following kinds of help: (a) personal care, for example, dressing, bathing or showering, eating, getting in or out of bed, using the toilet; (b) practical household help, for example, with home repairs, gardening, transportation, shopping, household chores; and (c) help with paperwork, such as filling out forms, settling financial or legal matters. First, the participants are asked whether there are people to whom they gave support during that period of time. If they answer affirmatively, they are asked about the recipients’ identity. The current study focuses on the question of support provided by the interviewed person to older family members, that is, mother, father, uncle, or aunt (other kin typologies representing a negligible minority in the SHARE sample concerning these two countries). The resulting research variable to be explained has been accordingly labeled “supporting elder relatives who live outside of the household.” It is a dichotomous variable that takes on two values: “1” if the respondent reports having given support to one or more older relatives in the 12 months preceding the interview; “0” if this is not the case. If the respondent reports having given support both to elder relatives and to others during that time, the support is seen as having accrued to the elder relatives. This variable was estimated for Time 1 and Time 2 on the basis of all respondents in the relevant wave who reported that they gave support to older relatives outside of their households.

Explanatory variables

Within those available in the SHARE data set, a number of potentially explanatory variables have been identified, in correspondence with the factors most likely to be associated with the outcome variable indicated above, in the light of the evidence provided by the literature reported in the introduction. They have been divided into following five groups (see Table 1).

Table 1.

Correspondence Between the Groups of SHARE Variables Considered by This Study and the Determinants Included in the Informal Care Model.

Determinants of informal care provision according to the ICM	Groups of explanatory SHARE variables considered by this study
	Sociodemographic characteristics	Health	Socioeconomic status	Social participation	Given or received social/financial support
Attitudes and affection
Normative beliefs
Barriers to care provision
Distance
Time	Marital status		Having a paid job	Being engaged in volunteering	Looking after a family with young children
Money			Being employed		Experiencing financial problems
Competence		Physical and mental health capacities
Context
Family	Marital status, family size				Presence of other family caregivers
Social network					Presence of other relatives, neighbors, and other non-kin
Care in the community					Lack of formal care (public, private, or voluntary services)

Note. ICM = informal care mode; SHARE = Survey of Health, Ageing and Retirement in Europe.

The first group includes the sociodemographic characteristics of gender (a dummy variable with men as base group), age (a continuous variable), household size, and family situation (a dichotomous variable that takes on two values: “0” if the individual is not married and “1” if he or she is married).

The second group comprises five variables relating to the respondent’s health. The first is a subjective assessment of health status on a 1 to 5 scale: excellent, very good, good, so-so, and poor (the higher the value, the worse the state of health represented). The second denotes the number of chronic illnesses that the respondent suffers from (on the basis of a closed list shown to the respondent). The third variable, capturing the presence of limitations in performing activities of daily living (ADL), reports whether the respondent experiences difficulties in carrying out at least one of the following activities: walking 100 m, sitting for approximately 2 hr, rising from a chair after protracted sitting, climbing several stories on stairs without resting, bending over, kneeling, stooping, touching or raising arms above shoulder level, pushing or pulling large objects, lifting a heavy weight, and lifting a coin from a table. The variable represents the total number of difficulties that the respondent reports. The fourth variable, concerning the presence of limitations with instrumental activities of daily living (IADL), denotes the difficulty experienced in performing activities of greater complexity: dressing, bathing, eating, getting out of bed, using the restroom including sitting down and standing up, using a map, preparing a hot meal, buying necessities, using the telephone, taking medicines, doing housework, and managing money. The variable represents the total number of difficulties that the respondent reports. The fifth variable, the individual’s depression index (the EURO-D (European Depression scale) index), is based on a series of questions that concern the older individual’s depression patterns, that together create a validated index (Dewey & Prince, 2005). Scores are on a 0 to 12 scale, with “0” denoting no depression and “12” maximum depression.

The third group brings together different types of socioeconomic information via four research variables. The first is education (a continuous variable representing the number of years of schooling). The second variable, employment, is a dichotomous one that takes on two values: “1” when the respondent is working and “0” otherwise. The total monthly posttax income of the respondent’s household represents the third variable, the fourth being the respondent’s subjective assessment of his or her household’s ability to make ends meet (on a range of four possible values: “easily,” “rather easily,” “with some difficulty,” and “with much difficulty”).

The fourth group comprises two variables concerning social participation. The first, doing volunteer work or charitable activity, is dichotomous and takes on two values: “1” when the person recently did one of the foregoing and “0” when she or he did not. The second variable, leisure activity, also dichotomous, takes on the value of “1” when the respondent carries out one or more of the following activities: participating in an in-service education or training activity; participating in activity of a sports club, social club, or other kind of club; taking part in organizing political activity or other activities for the community and “0” when the respondent did none of them.

The fifth and final group of variables considered for this study includes information on the social or financial support given or received. The first of the indicators included under this heading concerns the social support that the individual gave to others (who are not his or her elder relatives) who lived outside the person’s household in the 12 months preceding the interview. For this purpose, four dichotomous research variables are defined, according to the recipient of the support provided: children, grandchildren, other relatives, and non-relatives. For each variable, “1” represents a situation in which the interviewee gave social support, and “0” denotes the contrary. A second variable refers to the social support that the respondent or his or her spouse received from people in the 12 months preceding the interview. This variable—labeled as “receiving social support”—is dichotomous, and takes on the value of “1” when the respondent has received such support and “0” otherwise. The third category of variables presents information on receiving and/or giving financial support and includes two indicators. The first relates to financial support that the respondent or his or her spouse received from a relative or another person in the 12 months preceding the interview. This variable is dichotomous, “1” representing receipt of support and “0” otherwise. The second relates to support that the respondent or his or her spouse gave to a relative or another person in the 12 months preceding the interview. This variable is dichotomous, “1” representing having given support and “0” otherwise.

Table 1 provides an overview of the correspondence between the five groups of SHARE variables considered for this study and the determinants taken into consideration by the conceptual framework underpinning the informal care model. Given the primarily non-psychological focus of the SHARE survey, we can observe that the variables employed in this study refer only to the two dimensions concerning the barriers to care provision and the context.

Data Analysis

To understand the dynamics behind the peculiar evolution affecting Italy and Israel, in a first step, a bivariate analysis of the sociodemographic, health, socioeconomic, psychosocial, and support characteristics among persons aged 50+ years at Time 1 and at Time 2 was carried out, contrasting caregivers (i.e., those who provided social support as previously defined) with non-caregivers (i.e., those who did not provide it). To more rigorously analyze the role played by the different factors considered in informal care provision, we adopted a model that examines the probability that persons aged 50+ years provide support to elder relatives who live outside their household. To test the relative contribution of the existing information in each of the groups of research variables, an estimation equation that includes the research variables from all groups of variables was estimated. This allows us to test the relative contribution of each of these variables beyond those included in the other groups of variables. In addition to the estimation equation described above, the probability of providing support to elder relatives was also estimated as a function of each of the five groups of research variables only. This allows us to appraise the relative contribution of the existing information in the specific group of variables to the probability of supporting elder relatives, overlooking the possibility of the existence of additional variables that may explain this probability. The results of this estimation appear in Appendix A. The estimations were performed for Time 1 and Time 2 in each of the two countries to determine whether, and to which extent, the considered variables lost their explanatory power over time and to check for the possible existence of other variables that acquire explanatory power as time passes. In addition, we added a logistic regression to predict caregiving, including interactions of the variables with the two countries. Significant interactions mean that these countries differ in the impact of a certain variable on caregiving. The results of this estimation appear in Appendix B.

Results

The share of the over-50-year-old population providing social support to older relatives who live outside one’s household is shown in Figure 1, with regard to all countries for which SHARE data were available both in 2006 to 2007 (Time 1) and in 2015 (Time 2). Following a widely accepted typologization of welfare regimes (Srakar, Hrast, Hlebec, & Majcen, 2015), the investigated countries can be divided into four groups: Continental (Austria, Germany, Switzerland, Belgium, and France), Social Democratic (Sweden and Denmark), Mediterranean (Italy, Spain, Greece, and Israel), and Central-Eastern European (Czech Republic and Poland). While countries belonging to the Continental, Social Democratic, and Central-Eastern European welfare regimes show no uniform, consistent pattern of change between Time 1 and Time 2, all those grouped under the Mediterranean model report an evident drop between Time 1 and Time 2. In particular, the drop in the share of the population supporting non-co-resident older relatives is relatively strong in Italy (–30%), and especially in Israel, where it has more than halved in the considered period. This drop has been among the strongest across European countries, where the share of older adults providing social support has been predominantly stable or decreasing less remarkably over time, or even increasing in some cases.

Figure 1.

Share of over-50-year-old population giving support to older relatives who live outside their household in 2006-2007 (Time 1) and 2015 (Time 2), by country (%).

With regard to Italy, a statistically significant differentiation exists between caregivers and non-caregivers for most of the considered variables (Table 2). In particular, Italian caregivers are more likely to be younger, women, married, and living in larger households than non-caregivers. Apparently, contradictory results emerge with regard to health status: On one hand, caregivers report a better subjectively perceived health and less IADL impairments; on the other hand, they are characterized by a slightly higher level of depression. In terms of socioeconomic status, caregivers are on average better educated, more often in employment, and, not surprisingly, economically better off, both in terms of objective income level and subjective perception of their own household’s ability to make ends meet. Finally, caregivers are socially more active—both in terms of engagement in volunteer work and of leisure activities—and interact more frequently with others by providing and/or receiving financial/social support.

Table 2.

Relationship Between Supporting Role and Selected Characteristics of SHARE Respondents in Italy at Time 1 and Time 2 (Means, Standard Deviation, and Percentage Values).

			Time 1			Time 2
			Gave support	Did not give support	F/χ²	Gave support	Did not give support	F/χ²
Background	Age (M, SD)		63.49 (8.78)	67.16 (9.47)	2.88***	65.11 (9.10)	68.24 (10.01)	2.69***
	Gender	Female	57.67	50.13	6.50**	60.47	52.41	24.53***
	Gender	Male	42.33	49.87	6.50**	39.53	47.59	24.53***
	Household size (M, SD)		2.78 (1.12)	2.54 (1.11)	5.19***	2.51 (1.00)	2.36 (1.07)	7.56***
	Marital status	Married	84.54	78.97	12.05***	80.28	76.14	9.07***
	Marital status	Not married	15.46	21.03	12.05***	19.72	23.86	9.07***
Health	Self-rated health (M, SD)		3.20 (1.05)	3.36 (1.09)	5.03***	3.16 (0.99)	3.27 (1.04)	4.80***
	Chronic (M, SD)		1.82 (1.56)	1.94 (1.77)	1.13	1.55 (1.52)	1.58 (1.57)	0.85
	ADL problems (M, SD)		0.19 (0.78)	0.26 (0.93)	1.15	0.26 (0.99)	0.28 (1.00)	1.21
	IADL problems (M, SD)		0.30 (0.99)	0.49 (1.33)	2.70**	0.45 (1.61)	0.58 (1.74)	2.19**
	EURO-D (M, SD)		2.82 (2.41)	2.80 (2.66)	2.32**	3.03 (2.58)	2.74 (2.59)	2.39**
SES	Education (M, SD)		8.30 (4.36)	7.48 (4.24)	3.03***	9.84 (4.52)	8.71 (4.56)	4.01***
	Employment	Employed	21.33	16.61	9.09***	27.50	20.56	26.09***
	Employment	Not employed	78.67	83.39	9.09***	72.50	79.44	26.09***
	Income (M, SD)		9.83 (1.09)	9.66 (1.15)	2.77***	9.80 (1.13)	9.67 (1.17)	4.23***
	Makes ends meet (M, SD)		2.30 (1.86)	2.22 (0.87)	2.37	2.45 (1.00)	2.36 (0.97)	3.71**
Social participation	Volunteering	Yes	11.95	5.66	33.44***	19.30	9.50	81.90***
	Volunteering	No	88.05	94.34	33.44***	80.70	90.50	81.90***
	Leisure activities	Yes	13.43	8.38	17.13***	21.36	11.44	77.59***
	Leisure activities	No	86.57	91.62	17.13***	78.64	88.56	77.59***
Support	Receiving social support	Yes	24.04	18.40	11.94***	20.38	15.94	13.08***
	Receiving social support	No	75.96	81.60	11.94***	79.62	84.06	13.08***
	Giving financial support	Yes	31.38	19.29	49.58***	38.38	23.46	105.90***
	Giving financial support	No	68.62	80.71	49.58***	61.62	76.54	105.90***
	Receiving financial support	Yes	7.45	3.74	17.73***	9.00	4.45	37.30***
	Receiving financial support	No	92.55	96.26	17.73***	91.00	95.55	37.30***
n			2,783			5,225

Source. Own elaborations based on data from SHARE for Italy (2007, 2015).

Note. Parentheses denote standard deviation value. SHARE = Survey of Health, Ageing and Retirement in Europe; ADL = activities of daily living; IADL = instrumental activities of daily living; SES = socioeconomic status.

p < .05. **p < .01. ***p < .001.

Over time, changes seem to affect Italy’s caregiver and non-caregivers in a largely similar way. Compared with 2006, in 2015, both groups became older,¹ included a higher share of women, lived in smaller households, and were less frequently married. Self-perceived health remained almost unchanged, and the average number of chronic diseases dropped, while no significant association was found with problems in performing ADLs and IADLs and with the presence of depressive symptoms. Overall, the socioeconomic status improved for all considered indicators, as did the use of free time. Finally, financial support was provided and received to a larger extent, whereas social support was less frequently received.

Most of the trends described for Italy recur for Israel, too, as highlighted by Table 3. There are, however, some exceptions. First, Israel’s caregivers are the only group reporting a worse self-rated health in 2015. Second, together with Israel’s non-caregivers, they report an increase in the number of chronic diseases (which dropped instead in Italy for both groups), and a remarkable worsening in terms of IADLs performance (which, however, got especially worse among non-caregivers). Third, Israel’s non-caregivers report in 2015 an improvement in their depression level, which drops under that scored by caregivers (contrarily to what occurred in 2006/2007). A fourth major difference concerns the employment level that dropped heavily for both groups in Israel (compared with the increase observed in Italy). Fifth, leisure activities dropped slightly for Israel’s caregivers (compared with an increase for all other groups in the two countries). Finally, there is a remarkable decrease in the financial support provided by Israel’s both groups (compared with an increase in Italy).

Table 3.

Relationship Between Supporting Role and Selected Characteristics of SHARE Respondents in Israel at Time 1 and Time 2 (Means, Standard Deviation, and Percentage Values).

			Time 1			Time 2
			Gave support	Did not give support	F/χ²	Gave support	Did not give support	F/χ²
Background	Age (M, SD)		62.61 (9.56)	65.80 (9.90)	2.08***	68.53 (8.61)	70.68 (10.09)	1.20
	Gender	Female	57.31	54.62	0.93	62.30	56.55	4.04*
	Gender	Male	42.69	45.38	0.93	37.70	43.45	4.04*
	Household size (M, SD)		2.79 (1.39)	2.46 (1.32)	3.45***	2.44 (1.23)	2.20 (1.11)	2.48*
	Marital status	Married	81.21	76.78	3.64*	75.14	71.78	1.68
	Marital status	Not married	18.79	23.22	3.64*	24.86	28.22	1.68
Health	Self-rated health (M, SD)		2.87 (1.19)	3.16 (1.21)	5.38***	3.10 (1.11)	3.16 (1.20)	4.58***
	Chronic (M, SD)		1.76 (1.65)	1.96 (1.74)	1.32	2.04 (1.77)	2.04 (1.95)	0.93
	ADL problems (M, SD)		0.23 (0.88)	0.33 (1.08)	0.64	0.28 (0.98)	0.56 (1.46)	2.30*
	IADL problems (M, SD)		0.36 (0.99)	0.61 (1.35)	2.58*	0.63 (1.53)	1.27 (2.43)	3.55***
	EURO-D (M, SD)		2.72 (2.43)	3.10 (2.67)	0.86	2.93 (2.16)	2.44 (2.48)	5.41***
SES	Education (M, SD)		11.63 (4.47)	10.36 (4.56)	7.80***	13.24 (4.24)	12.16 (4.44)	2.31***
	Employment	Employed	48.49	32.87	33.39***	31.15	24.64	6.63**
	Employment	Not employed	51.51	67.13	33.39***	68.85	75.36	6.63**
	Income (M, SD)		10.05 (1.13)	9.70 (1.14)	6.32***	10.18 (0.96)	9.96 (0.99)	2.64**
	Makes ends meet (M, SD)		2.50 (1.03)	2.31 (0.96)	6.63***	2.80 (1.03)	2.79 (1.04)	2.93*
Social participation	Volunteering	Yes	18.74	10.81	17.65***	26.84	12.74	42.99***
	Volunteering	No	81.26	89.19	17.65***	73.16	87.26	42.99***
	Leisure activities	Yes	41.53	24.45	45.26***	39.62	27.43	21.33***
	Leisure activities	No	58.47	75.55	45.26***	60.38	72.57	21.33***
Support	Receiving social support	Yes	22.27	22.57	0.02	22.40	23.85	0.35
	Receiving social support	No	77.73	77.43	0.02	77.60	76.15	0.35
	Giving financial support	Yes	48.26	31.40	39.43***	34.15	20.02	34.19***
	Giving financial support	No	51.74	68.60	39.43***	65.85	79.98	34.19***
	Receiving financial support	Yes	7.89	5.97	1.94	11.75	5.76	16.80***
	Receiving financial support	No	92.11	94.03	1.94	88.25	94.24	16.80***
n			1,654			2,014

Source. Own elaborations based on data from SHARE for Israel (2006, 2015).

p < .05. **p < .01. ***p < .001.

The results of the models’ estimation are shown in Figures 2a to 2f. Variables that were found to be statistically significant appear in solid color; those found not significant are shown in broken lines. The probability of providing support to older relatives who live outside one’s household is associated with several factors, as highlighted in the following.

Figure 2.

Probability (odds ratio) of giving support to elder relatives (aged 50+ years) living outside the household (mother, father, aunt, and uncle); (a) Sociodemographic, (b) Health, (c) Socioeconomic status, (d) Social participation, (e) Giving social support, and (f) Receiving social support/financial transfers.

With regard to sociodemographic characteristics, the association remains statistically significant for both countries over time (i.e., both in 2006-2007 and in 2015) only for age (i.e., the older you are, the less likely is that you provide care), with no remarkable change over time. Gender emerges as another “constant” of our findings, as women are increasingly more likely to act as caregivers in both countries, with a stronger growth of probability in Italy than in Israel. Opposite trends over time are recorded for the two countries with regard to household size and marital status: In Israel, in particular, the former gains importance in explaining the probability of being a caregiver (the bigger the household, the higher this probability), whereas being married decreases the probability of being a caregiver (albeit only in 2015).

Overall, the presence of health-related problems was found to be negatively associated with the probability of acting as a caregiver only in Italy in 2015. Depression represents a condition, which is always more common among caregivers in both countries; whereas the presence of ADL difficulties became positively associated to this status for Israel in 2015 only, the opposite being true in the same country for IADL performance.

As for socioeconomic status, a first common result over time and for both countries concerns the recognition that the higher the educational level, the higher is the probability of being a caregiver. A similar pattern applies to both income level and the economic ability to make ends meet (the higher this ability, the more likely the chance of being a caregiver). Contrasting—albeit converging—trends can be observed with regard to employment: In Israel, the probability of being a caregiver, once positively associated with being in employment, becomes today negative, thus possibly suggesting increasing difficulties in reconciling unpaid care and paid professional roles for the labor market, whereas in Italy the opposite trend seems to be taking place.

Being involved in voluntary work and spending time in leisure activities are both “crowding in” with the caregiver role in both countries and over time, with no exception (albeit in recent times the strength of the positive association with leisure activities has been weakening in Israel).

Finally, in both countries, caring for an older relative is positively associated with the role of being caregiver for another (non-older) relative in recent times, but not for other categories of recipients (such as children, grandchildren, or non-relatives). This condition of being a multiple caregiver represents, among all considered variables, the most relevant factor associated, in terms of odds ratios, with the probability of caregiving. Financial support plays a role in this regard, too, as it crowds in with the provision of social support, especially (but not only) when it is given.

Discussion

Dramatic population aging is a hallmark of recent years. This demographic process has brought to the fore many questions concerning the social, health, and economic implications of later adulthood, of which the current study examines those specifically concerning the condition of family caregivers, comparing Italy with Israel.

This study shows that the probability of offering social support to elder family members who live outside the household has been trending down substantially in both countries over the years. The explanations for this decline could be many and interlinked to each other. First, especially Italy has sustained a remarkable blow from the financial crisis of the “aughts.” This would imply that Italian (but partly also Israeli) households’ ability to grant social support to elder kin has been increasingly limited, following the growing involvement of many potential caregivers in the labor force. This would be supported by a possible second explanation, focused on the weakening family support structures following the aging process of many family members and their consequent reduced ability to provide informal care (Albertini, 2016). On one hand, this is reflected by the progressive aging of grandparents, who in the familist care model existing both in Italy and in Israel often act as substantial caregivers to younger family members (Casanova et al., 2019). On the other hand, this applies to the aging of adult caregivers, who find themselves more and more frequently “trapped” into efforts to manage and conciliate different professional and care responsibilities in a complex daily life (OECD, 2017).

The insights emerging from the model analyzed in this study seem to confirm the above outlined framework. Not surprisingly (Albertini, 2016), the probability of providing social support is negatively correlated with individual’s age, with women more likely to offer support. A positive correlation between household size and the tendency to provide social support was detected only in Israel, confirming that immediate proximity represents a facilitating factor for informal care provision in this country. Contrarily to what is suggested by previous studies (Bauer & Sousa-Poza, 2015), our findings show that, in both Italy and Israel, health condition is no key factor in shaping individuals’ decisions to grant or refrain from granting social support to older relatives. This might reflect the high importance attributed by Israelis and Italians to informal care provision, irrespective of one’s health status, albeit differences exist on the meaning attached to this task (Casanova et al., 2019): In Italy, informal care is often assimilated to that provided by privately hired migrant care workers (Di Rosa, Barbabella, Poli, Santini, & Lamura, 2018) and refers primarily to hands-on care and “soft” health care, whereas in Israel it is more focused on relational aspects (Shamir, 2013).

Socioeconomic factors were found to have an overall weighty effect, with one main exception: While the probability of granting support to older relatives correlates positively with the carer’s educational level in Israel, this variable plays no role in Italy. Employment status and income (in both its more objective and subjective components) contribute instead to explain individuals’ inclination to provide informal support in both countries. This reinforces the claim that people often tend to act on the basis of rational calculus, so that, when they are in the position to assist others financially, they tend to follow through (Albertini, 2016). Other explanations may also touch upon the synergic contribution of three factors: the low level of formal care available, especially in Italy; the upward trend in both countries’ level of prices for health and welfare products; and the ongoing crowding-out of public funding in both Israeli and Italian care systems. These processes represent for family members an incentive to provide unpaid care to older relatives, whose financial situation is presumably worse than their own. Confirming previous studies, the availability of formal care services is positively correlated with informal caregivers’ well-being, via a higher perceived control (Wagner & Brandt, 2015, 2018).

Being involved in social and/or leisure activities turns out to play a role, too. In both countries, when one performs volunteer or charitable work and/or engages in leisure activities, the likelihood of providing unpaid care is significantly higher today even more strongly than in the past. This seems to confirm the influence of the “culture of caring” on the individual choice to provide informal care (Boll, Ferring, & Valsiner, 2018; Miller, 2017), yielding the picture that social participation performed for one’s personal pleasure leverages social support provision.

As for financial transfers, they raise the probability of supporting older relatives also socially in both countries, while receiving financial help makes the latter more likely only in Israel. This might hint to a sort of interchangeability, in this country, between the two forms of support (Albertini, 2016), that might contribute to explain the impact of the recent economic crisis on the ability of older adults to provide informal care.

On the whole, our findings offer a first, though partial, empirical test to validate the theoretical framework provided by the recently proposed informal care model (Broese van Groenou & De Boer, 2016). While, on one hand, they seem to confirm the importance of most determinants included under the domains of perceived barriers and of contextual factors, on the other hand, they suggest that more focused research is needed to understand the direction of some of these associations, and that future investigations should also include, under the umbrella of a multidimensional approach, crucial components, such as caregivers’ attitudes and normative beliefs.

Finally, it should be underlined that the present study presents some limitations. The first concerns the quantitative-only methodology used for this study, which did not allow to gather more in-depth information on why respondents provide or do not provide informal care. Second, the analyzed data provide information only on support provided to non-co-residing relatives. As a consequence, our analysis could not gain any insight on the informal care provided to co-residents or on the interaction between co-resident and non-co-resident care (and on the role played, in this regard, by changes in living arrangements occurring in the two countries over time). A third limitation is that it focused on developments in Italy and Israel only. This narrower focus is justified by the composition of the research team conducting the study, based in the two selected countries, thus possessing an expertise on national LTC systems allowing them to infer more in depth about the reasons explaining the observed findings. To bridge this gap, future analyses might consider all countries reporting a similar decreasing trend, or contrasting those reporting a drop with those characterized by an increased availability of informal carers, to investigate whether the predicting factors behind both trends are the same or not. A fourth limitation concerns the focus on provision of help to older family members only. As some respondents might not have living older relatives (being older adults themselves), the findings provided here do not provide a fuller picture of informal support to older adults (which might be achieved by analyzing also the help received from younger family members, this, however, representing a topic that goes beyond the scope of this article). Finally, the analysis proposed here refers to cross-sectional data only, so that our findings resemble essentially two pictures taken at two different time points, with subjects providing care during 2006 to 2007 possibly being, in principle, completely different from those doing it in 2015. Therefore, the research question investigated in this article refers to the probability of giving social support at two different time points (and the factors associated with it), although a longitudinal analysis of panel data would have allowed to infer how and why the same people, as they grow older, behave as informal carers at two different time points (this being a different research question). Although the longitudinal approach would have reduced the sample size in our case to such an extent that statistical analyses would have been possible only for a limited number of variables, it might represent an interesting method for a future study ensuring a statistically manageable sample size.

Despite these limitations, we believe that this study allows to highlight to an extent that in our knowledge no previous research has done so far, that Israel and Italy—depicted traditionally, like other Mediterranean societies, as comparatively more able of activating family channels to tackle the LTC needs of close relatives—have experienced a remarkable decline in informal care provision, and to identify which factors are associated to this phenomenon. Further research will be needed to understand the reasons of this decline, including whether this might be due to the impact of macro-level policies, an analysis that is beyond the scope of this study.

Footnotes

Appendix

Appendix B

Logit Model for Probability of Giving Support to Elder Relatives (Age 50+) Living Outside the Household (Mother, Father, Aunt and Uncle), Including Country Interactions.

	Time 1	Time 2
Age × Country^a	0.921*** (0.01)	0.888*** (0.02)
Gender × Country^a	1.437 (0.29)	1.516 (0.38)
Household Size × Country^a	1.220*** (0.08)	1.389*** (0.13)
Marital × Country^a	1.196 (0.39)	0.495* (0.16)
Self-Rated Health × Country^a	0.986 (0.09)	0.976 (0.14)
Chronic Diseases × Country^a	1.029 (0.08)	0.916 (0.09)
ADL Problems × Country^a	0.906 (0.39)	1.543 (0.35)
IADL Problems × Country^a	0.671 (0.23)	0.630* (0.13)
EURO Depression × Country^a	1.054 (0.05)	1.290*** (0.08)
Education × Country^a	1.054* (0.03)	1.119*** (0.04)
Employment × Country^a	1.904*** (0.41)	0.873 (0.23)
(Ln)income × Country^a	1.235** (0.11)	1.413*** (0.17)
Makes Ends Meet × Country^a	1.168 (0.13)	1.412* (0.20)
Help-children × Country^a	1.216 (0.42)	2.061 (0.99)
Help-grandchildren × Country^a	1.274 (1.45)	0.972 (1.21)
Help-other_relatives × Country^a	1.687 (0.64)	4.178*** (2.08)
Help-non_relatives × Country^a	0.944 (0.51)	1.168 (0.54)
Volunteer × Country^a	1.502 (0.36)	1.704* (0.47)
Leisure × Country^a	1.962*** (0.39)	1.458 (0.37)
Rec_help × Country^a	0.577 (0.21)	0.818 (0.33)
Financial_rec × Country^a	1.864* (0.60)	1.617 (0.61)
Financial_give × Country^a	1.396 (0.27)	1.096 (0.28)
n	4,236	6,365

Source. Own elaborations based on data from SHARE for Italy (2007, 2015) and Israel (2006, 2015).

Note. Standard errors are in parentheses. ADL = activities of daily living; IADL = instrumental activities of daily living; SHARE = Survey of Health, Ageing and Retirement in Europe. Higher score in each variable represents a poorer condition, except for age, household size, education, (ln)income, and makes ends meet.

Country: 1 = Israel, 0 = Italy; Gender: 1 = female, 0 = male; Marital: 1 = married, 0 = not married; employment: 1 = employed, 0 = not employed; help-children: 1 = yes, 0 = no; help-grandchildren: 1 = yes, 0 = no; help_other_relatives: 1 = yes, 0 = no; help_non_relatives: 1 = yes, 0 = no; volunteer: 1 = yes, 0 = no; leisure: 1 = attended an educational or training course/gone to a sport, social or other kind of club/taken part in a political or community-related organization, 0 = none of these; rec_help: 1 = received help, 0 = no; financial_rec: 1 = received financial support, 0 = no; financial_give: 1 = gave financial support, 0 = no.

p < .05. **p < .01. ***p < .001.

Authors’ Note

This article uses data from SHARE (Survey of Health, Ageing and Retirement in Europe) and SHARE Waves 1, 2 and 6 (DOIs: 10.6103/SHARE.w1.611, 10.6103/SHARE.w2.611, 10.6103/SHARE.w6.611), see for methodological details.

Author Contributions

A.T.-S., G.C., and G.L. initiated and wrote the manuscript jointly. All authors read and approved the final manuscript.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The SHARE (Survey of Health, Ageing and Retirement in Europe) data collection has been primarily funded by the European Commission through FP5 (QLK6-CT-2001-00360), FP6 (SHARE-I3: RII-CT-2006-062193, COMPARE: CIT5-CT-2005-028857, SHARELIFE: CIT4-CT-2006-028812) and FP7 (SHARE-PREP: N°211909, SHARE-LEAP: N°227822, SHARE M4: N°261982). 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) and from various national funding sources is gratefully acknowledged (see ).

ORCID iD

Aviad Tur-Sinai

Notes

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