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. Author manuscript; available in PMC: 2013 Jan 10.
Published in final edited form as: Soc Indic Res. 2010 Aug;98(1):89–104. doi: 10.1007/s11205-009-9519-5

The Subjective Well-Being of Immigrants Aged 50 and Older in Israel

Karin Amit 1, Howard Litwin 2
PMCID: PMC3541716  NIHMSID: NIHMS431465  PMID: 23316100

Abstract

The present study evaluated the integration of elderly people who migrated to Israel during their lifetimes. Subjective well-being, as measured by the immigrants’ perception of quality of life, satisfaction with life and emotional state, served as a general indicator of integration. The integration of elderly immigrants has not received adequate attention in the literature. A unique database (SHARE-Israel) that was recently released has made study of this topic possible. The current study sample was composed of former migrants aged 50 and older (n = 930). The analytic model examined ethnic origin and migration variables in relation to the respective subjective outcomes, controlling for sociodemographic background, human and social capital and health. The findings show that in general, ethnic origin seems to matter less for the evaluation of immigrants’ subjective well-being than other socio economic factors such as economic status, social capital and health status. However, recent arrivals from the Former Soviet Union do differ from all other immigrant groups in their lower levels of well-being. In addition, the study points to the importance of language proficiency as a central means for integration in the destination country.

Keywords: Well-being, Quality of life, Life satisfaction, Depression, Elderly

1 Introduction

The process of immigrant integration into a host society has been studied for many years, from many perspectives, and with relation to a multiplicity of factors and characteristics that influence the process. In addition to immigration characteristics (such as number of years since migration, age at migration and language skills) and the demographic characteristics of the immigrant (such as gender and age), economic, social and psychological characteristics have also been found to be linked to the process. The current study examines these characteristics as predictors for subjective social integration of elderly immigrants, and addresses the question: what are the determinants of immigrants’ subjective well being at the destination country?

Subjective well-being has three basic components, affective, cognitive and emotional (Diener et al. 1985). Perceived quality of life represents the affective component of well-being, general satisfaction with life represents the cognitive component and level of depression represents the emotional component. Quality of life is defined as “individuals’ perception of their position in life in the context of the culture and value systems in which they live and in relation to their goals, expectations, standards and concerns” (WHOQOL 1998: 1570). Life satisfaction is defined as an overall assessment of an individual’s quality of life according to his or her personal judgment and criteria (Shin and Johnson 1978). According to Diener (1984), life satisfaction is best measured by asking individuals to rate their satisfaction with life as a whole, as opposed to summing their satisfaction across specific imposed areas. This understanding is shared by other researchers in the field (e.g., Kahneman and Krueger 2006; Bohnke 2008). Depression, or the emotional aspect of well-being, is a mental state characterized by a pessimistic sense of inadequacy and a despondent lack of activity. It is most frequently assessed by the presence of symptoms such as feelings of guilt, irritability and fatigue. The prevalence of depressive symptoms may vary across populations (Castro-Costa et al. 2007).

What are the determinants of an individual’s subjective well being? This question has been addressed in many studies (e.g., Bonini 2008; Litwin 2005).The cognitive component of well-being, life satisfaction, was found to be associated with income (Diener et al. 1993) and with one’s standard of living (Bohnke 2008). Education often results in improved social relationships and higher earnings, which in turn enhance satisfaction (Helliwell 2003). Marital status, health conditions and social capital (contacts and social activities) are all significant predictors of life satisfaction among elderly people (Litwin 2005). A cross-national study recently found that 81% of the variation in mean life satisfaction was due to individual attributes (such as gender, age, marital status, income and education), but some 19% was due to country characteristics (GDP, human development indexes) (Bonini 2008). This latter finding implies that predictors of life satisfaction may be different among people who come from different countries of origin, and among immigrants, in particular.

The affective component of well-being, quality of life, was found to be associated with measures of economic status (Wiggins et al. 2004), including education, income and net worth (Knesebeck et al. 2007). This study note that these associations may vary by country. As for the emotional component of well-being, depressive state, a study of Mexican Americans found that gender, financial strain, chronic health conditions and disability were all related to depression. Of particular interest is that the depressive symptoms were also associated with immigrant status, recency of immigration and levels of acculturation and assimilation (Black et al. 1998). Following these studies we can hypnotize that ethnic origin may be associated to different levels of well-being.

Recent studies on the social integration and well-being of immigrants is currently giving increasing attention to subjective indicators alongside objective measures as income level (e.g., Anson et al. 1996; McMichael and Manderson 2004; Neto 1995, 2001). That is, there is greater recognition of the need to examine how immigrants feel. For example, Massey and Redstone (2006) studied the integration of immigrants in the United States, taking into account both socio-economic variables and a subjective measure of life satisfaction. Their results showed that immigrants who expressed greater life satisfaction had a greater tendency to become naturalized in the US and to settle there. That study and others demonstrate the need to examine immigrants’ perceptions regarding their integration and satisfaction (Lester 2005). Consideration of subjective aspects of social integration is particularly important for the study of immigrants of retirement age, insofar as common objective measures of integration are frequently related to active employment status (Remennick 2003).

Nevertheless, one of the central objective indicators of successful integration is the economic status. In fact, the expectation of attaining a better financial situation is a key motivating factor for leaving one’s country of origin. Economists thus define successful integration as the ability of immigrants to attain salary levels comparable to those of native-born citizens with similar characteristics. However, the attainment of economic success is generally a long-term process that is enhanced by the number of years since migration and in the immigrants’ age upon arrival. Given that the number of years in the destination country improves the economic position of immigrants, and given that better economic conditions (as represented by income and standard of living) are related to greater well-being (Diener et al. 1993; Bohnke 2008), we may hypothesize that the higher the immigrants’ economic position and the longer they have been in the destination country, the greater their subjective well being will be.

While some studies show significant economic improvement with each year in the new country and eventual disappearance of the income-gap vis-à-vis the natives (Chiswick 1979), other studies indicate that certain immigrant groups have difficulties in narrowing this gap and even transmit this disparity to their children (Borjas 1994). The groups that succeed in closing the economic gap faster are those arriving from developed countries with higher technological levels and relevant skills applicable to the new country (Semyonov and Lerenthal 1991). Language also plays a central role in the integration of the immigrant in the new labor market and his or her ability to narrow economic gaps vis-à-vis the natives (Chiswick 1998, 2002). The relevant skills and qualifications, together with the appropriate level of higher education and language proficiency, all comprise the human capital of the immigrant. Given that education is related to well-being in the general population, as noted earlier (Helliwell 2003), we may hypothesize that the higher the immigrants’ education level the higher their subjective well being will be. Moreover, since language proficiency is a unique immigration variable related to economic success, we may further hypothesize that language proficiency will also be positively related to the immigrants’ well being.

Another aspect that might explain the integration of immigrants is their level of social capital. The construct of social capital was defined by Bordieu (1986) as the total resources, feasible or potential, that an individual or a group accumulates by means of constant maintenance of social networks or reciprocal social interactions. Through social capital, individuals can more easily obtain economic and cultural resources, and they can better ensure receipt of benefits. Studies dealing with immigrant integration cite the relative deficit of social capital experienced by immigrants in a new country, as compared to the native-born. In order to compensate for this deficit, social networks are often formed at both the family and group level in order to assist and support the immigrant (Portes 1998). Previous studies indicate that social capital, as represented by social contacts and social activities, is a significant predictor of life satisfaction and quality of life among elderly people (Litwin 2005; Nilsson et al. 2006). In light of this, we can hypothesize that immigrants who are more socially active will report higher level of well-being than non socially active immigrants.

Finally, when examining the various determinants of well-being among elderly immigrants it is necessary to take into account their health status. This variable has been found to be significant in predicting the subjective well-being of elderly people (Landau and Litwin 2001) in general, and the well-being of elderly immigrants in particular (Litwin 2005). Consequently, health status must be controlled in the analysis. To sum up, the present study examines the integration of elderly immigrants into Israeli society via their perceived quality of life, their general satisfaction with life and their emotional status.

1.1 The Israeli Case

Jews from a wide range of countries have migrated to Israel since the latter part of the nineteenth century, with the rate and extent of immigration increasing significantly after the founding of the state (1948). The total Israeli population, estimated at 805,600 at the date of independence, had grown to 7,411,000 at the beginning of May 2009, largely due to immigration. In 2007, nearly 30% of the Jewish population in Israel were foreign born and 70% were local born, of which 34% were the sons and daughters of first generation immigrants (Amit et al. 2009). As such, Israeli society is clearly an immigrant society. The current study examines the integration of Jewish immigrants in Israel. As opposed to many earlier studies, which tend to focus upon younger aged immigrants, this study addresses the population of older adults who migrated at various points in their lifetimes. The inquiry is also innovative in that it examines subjective parameters of social integration. This is in contrast to many other studies, which limit their inquiry to the socio-economic indicators of successful absorption in the host society.

“Aliyah” or immigration to Israel may be divided into five main periods (Amit and Semyonov 2006). The first stage is counted up to the founding of the state, in 1948, with most of the immigrants arriving from Eastern and Central Europe (mainly the USSR, Poland, Romania and Germany). Many of these migrants were young and were motivated largely by social ideological aspirations. A smaller group of immigrants arrived from Yemen, driven mostly by religious conviction. The second stage reflects the mass migration to the new state of Israel that occurred immediately after its establishment, from 1948 to 1952. People arrived from Europe (mostly Holocaust survivors), and from Asia and North Africa (mainly Iraq, Iran, Yemen and Morocco). The latter group migrated for a mix of reasons that included political oppression, economic deprivation and religious orientation.

A third stage of immigration took place from 1953 to 1989, and was characterized by sporadic arrivals of groups from different countries and with widely ranging motivations for coming to Israel. This stage ended abruptly in late 1989 with the breakup of the Soviet Union and the exit of Jews from the Republics that until then had comprised the USSR. The mass arrival of Soviet Jews from 1990 to 1995 most prominently reflects the character of the fourth period of immigration to Israel, although a smaller number of immigrants arrived from Ethiopia in this same period as well. The fifth stage of immigration is that which has occurred since 1996. This period is marked by a sporadic mix of immigrants from the former Soviet Union, Europe (mainly France), the US, Argentina and Ethiopia. The motivations for migration among these most recent arrivals are as varied as the countries from which they came.

Several studies that examined the issue of integration of immigrants in Israel focused on the first three stages noted above. These studies underscored the existence of ethnic and socio-economic gaps in Israel society, noting particularly the division between two major socio-cultural groupings: the European and American-born (Westerners) and those who came from Africa or Asia (Easterners). The analyses showed that educational level, occupational status and salaries were lower among the Easterners than among the Westerners, both in the parent generation and among their children (e.g., Cohen and Haberfeld 1998). However, recent studies suggest that more specific categories of ethnicity or origin are required in order to understand the socio-economic differentials that exist in Israel and in other immigrant societies. These more precise categories are based upon one’s specific region of origin or continent (Amit 2005; Khazzoom 1998). In addition, the current mode of thought in Israel suggests the need to address the recent immigrants from the former Soviet Union as a separate group, due to their unprecedented numbers and their uniquely economic and political motivations for migration.

Nearly 1 million immigrants arrived in Israel from the FSU after the collapse of the Soviet Union in 1989 and they account for about 20% of the total Jewish population (Central Bureau of Statistics 2007). According to Rozenbaum-Tamari (2004), the economic and political uncertainty in the countries of origin led to an economic pattern of migration based on push factors. Studies point to the high levels of human capital with which FSU immigrants arrived in Israel relative to both the Soviet and Israeli populations (see e.g., Beenshtock and Ben Menahem 1997; Eckstein and Weiss 2002). Studies of FSU immigrant economic assimilation in Israel have documented impressive employment levels of immigrants, but partly at the cost of occupational downgrading compared with the occupations they held in the FSU (Raijman and Semyonov 1997; Eckstein and Weiss 2002). Contrary to previous immigration waves comprising mostly young people, a significant portion of the FSU are above the age of 40 (Remennick 2003).

In light of all the above, the present study examines the integration of elderly immigrants in Israel, via the prism of their subjective well-being. The study analyzes a series of possible factors as predictors of subjective well being, while differentiating between immigrants from different origin groups.

General research hypotheses:

  1. Ethnic origin will be associated with quality of life, life satisfaction and depression level among immigrants. Immigrants from origin groups with higher socio-economic status will report higher levels of well being.

  2. Years since migration will be positively associated with quality of life and life satisfaction among immigrants, and negatively associated with depression level. The immigrants’ age upon arrival will be associated to these variables is a reversed way.

  3. Language proficiency will be positively associated with quality of life and life satisfaction among immigrants, and negatively associated with depression level.

  4. Economic status will be positively associated with quality of life and life satisfaction among immigrants, and negatively associated with depression level.

  5. Human capital (as measured by education level) will be positively associated with quality of life and life satisfaction among immigrants, and negatively associated with depression level.

  6. Social capital (as measured by activity level) will be positively associated with quality of life and life satisfaction among immigrants, and negatively associated with depression level.

2 Method

2.1 Sample

The analysis is based upon data from a national probability household sample of persons aged 50 and over (and their spouses regardless of age), who participated in the first wave of the Israeli component of the Survey of Health, Aging and Retirement in Europe (SHARE). The international SHARE survey is conducted in 12 countries in Europe among elderly people, and addresses questions related to demography, physical and mental health, cognitive functioning, occupation and pension, social support and well being. The Israeli sample was drawn according to the uniform guidelines of the SHARE project (Börsch-Supan and Jürges 2005). The Israeli data were gathered in 2005/6 and comprised 2,492 respondents aged 50 and above. In the current analysis we look exclusively at the respondents who filled in the drop-off questionnaire employed in the survey, because two of the subjective well-being measures of interest to this investigation were included in that instrument. The proportion of respondents who returned the drop-off was some 63% of the effective respondent sample. Analyses revealed that the drop-off respondents were similar, on the whole, to the overall sample in terms of their sociodemographic characteristics (Litwin and Sapir 2008). In addition, we should note that the present inquiry was limited to respondents aged 50 and above (with no upper limit) who immigrated to Israel in their lifetime (N = 930). The data employed in the current analysis were unweighted, insofar as the investigation focused upon a subsample within the dataset and since the aim of the study was to consider associations among the variables.

2.2 Variables

As noted earlier, the outcome measures addressed in this inquiry reflect the three components of subjective well being: affective, cognitive and emotional. The corresponding measures employed were “quality of life”, “life satisfaction” and “depression”. For quality of life we utilized the CASP scale that was developed and validated in England in a representative sample of persons aged 65–75 (Hyde et al. 2003). The SHARE survey utilizes a 12 item version of the scale that includes its four main subscales: (C)ontrol, (A)utonomy, (S)elf-realization and (P)leasure. Each subscale is composed of three items, each of which is measured on scales of 1–4. The reliability score obtained for the 12 items in the Israeli sample was acceptable (α = 0.82). Examples of the probes include “I feel that what happens to me is out of my control,” and “I feel that my life has meaning”. The summary score employed in this analysis was the mean of the average scores for all four subscales. Respondents with missing data on this key variable were excluded from the analysis.

Life satisfaction was measured on a single item reflecting one’s global satisfaction (1–4). Kahneman and Krueger (2006) have recently discussed the use of a global question to measure life satisfaction in such surveys as the American General Social Survey. They note that respondents have little trouble answering this probe and that the correlation that is obtained in 2-week test and re-test reliability is sufficient.

Level of depression was assessed by means of the Euro-D scale, which was developed to measure depression among older populations in Europe. The scale is based on self-report of 12 symptoms, such as irritability, trouble sleeping, and excessive guilt feelings (Castro-Costa et al. 2007). The outcome variable employed in this analysis used a summary count of the symptoms.

The independent variables in the analysis included measures of immigration, sociodemographic background, human capital, social capital and health. The immigration variables employed were “years since immigration”, “age upon migration” and “proficiency of language.” The latter was computed as the average response to two probes that queried reading and writing levels on scales of 1–5, [the correlation between these two measures was very high (r = 0.88, P < .05). It is important to note that in the SHARE questionnaire this particular variable did not directly address proficiency in the Hebrew (local) language, but rather asked about language proficiency per se. However, we believe that most of the immigrant respondents interpreted the question to refer to proficiency in the Hebrew language.

The sociodemographic background variables included “age”, “gender”, “marital status” (married/not married), and “continent of origin” (Asia, Africa, Western Europe, Eastern Europe and the Americas). As noted earlier, immigrants from the Former Soviet Union after the start of the great wave of immigration in 1989 were treated as a separate group.

Economic status was measured by “household income”. The income variable reflected total household income from a range of sources in Euros. Human capital was measured by “educational level”. Education was recorded on a scale of 1–6, the higher the score, the greater the education. Social capital was addressed in terms of one’s variety of “participation in social activities”. The activities queried included voluntary or charity work; caring for a sick or disabled adult; providing help to family, friends or neighbors; participation in a sport or social club; participation in a religious organization; and participation in a political or community-related organization. Scores on this variable ranged from 0 to 6. Finally, “health” was recorded on a self-reported health measure that ranged from 1 to 5; the higher the score, the better one’s health.

The analysis was executed by means of hierarchical multiple linear regression for each of the three outcome variables. Three stages were implemented in each regression procedure. In the first stage, the region or continent of origin variable was entered; Western Europe served as the reference category. This was followed, in the second phase, by the entry of the immigration variables. In the third and final stage, all the remaining variables were entered into the regression.

3 Findings

Table 1 presents the immigration and background variables by origin groups. Several differences were observed. As expected, the table shows significant variation regarding years since immigration. Duncan tests of group mean differences (not shown in table) underscored that, predictably, the immigrants from the Former Soviet Union after 1989 had the least tenure in Israel while the rest of the groups had some 40 years and more of residence in the country. In addition, there are significant differences in the age upon migration. Immigrants from Asia, Africa and West Europe came at a very young age (around 15), immigrants from East Europe and America at a somewhat older age (around 20), but the majority of immigrants from the FSU (who came after 1989) arrived as elderly people (around 54). In terms of language proficiency, most of the groups were similar, except for those from Asia who indicated having lesser such skills.

Table 1.

Immigration and background variables by origin group among migrants to Israel aged 50 and older: averages and analysis of variance/Chi square

Variables Origin groups
Total Asia Africa East Europe West Europe America FSU (after 1989) F/Chi square df
 Number of cases 930 156 213 279 74 34 175 –
Immigration
 Years since 43.7 54.3 49.6 49.4 56.0 41.1 13.3 381.4** 928
Age at migration 24.2 13.8 15.1 20.1 14.4 24.5 54.0 296.8** 926
 Language skills 3.5 3.1 3.4 3.6 3.7 3.6 3.6 4.2** 926
Background
 % Females 55.1 52.7 51.9 55.8 64.6 54.6 55.8 4.0 5
 Age 66.1 66.3 62.8 68.4 68.4 63.9 65.4 9.3** 928
 % Married 75.0 76.8 75.1 72.6 69.8 85.6 77.1 4.3 5
 Income 26,647 24,409 27,286 29,531 34,906 40,840 17,023 7.0** 928
 Education 3.0 2.1 2.6 3.1 3.3 3.3 3.7 40.7** 925
 Activities 0.7 0.7 0.6 0.8 1.2 0.9 0.5 7.4** 928
 Health 3.1 2.9 3.1 3.1 3.5 3.3 3.2 4.1** 928
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*

P <.05;

**

P <.01

Turning to the background variables, no differences emerged across the origin groups regarding gender or marital status. However, the Europeans (East and West) were clearly the oldest in the sample, and the Africans were the youngest, on average. Significant differences were evident in terms of income. Immigrants from the Americas had the highest household income, followed by those from Western Europe. Persons from the Former Soviet Union had the lowest reported household income, and those who had arrived from Asia had only slightly higher incomes. Strong differences were also evident in terms of education. Immigrants from the Former Soviet Union were the most highly educated, followed by those from Europe and the Americas. Persons who came from Africa were less educated, and those who arrived from Asia indicated having had the lowest level of education in the sample.

As for social capital, the table shows that respondents from the Americas had the highest reported mean activity level. Significantly lower activity levels were found among immigrants from Asia and Africa, and the lowest mean level was reported by those from the Former Soviet Union. Turning to self-reported health, the table shows that persons from the Americas and Western Europe had the highest health levels, and respondents from the Former Soviet Union, Eastern Europe, Africa and Asia, respectively, had the lowest.

Table 2 summarizes the differences in the subjective outcome measures by origin group. The table presents the means for each group on the quality of life, life satisfaction and depression measures. Several differences emerged. First, immigrants from the Former Soviet Union reported the lowest quality of life. The highest relative quality of life was indicated by persons who had arrived from Western Europe and the Americas, followed closely by those from Africa and Eastern Europe. Differences were much less apparent by origin group on the life satisfaction measure, but those from Asia nevertheless revealed the least such satisfaction. In contrast, strong differences were evident across the groups regarding reported depressive symptoms. People from the Americas and from Western Europe reported having the fewest depressive symptoms, while the greatest number of symptoms was reported by immigrants from Asia, the Former Soviet Union and Africa, respectively.

Table 2.

Life quality, life satisfaction and depression by origin group among migrants to Israel aged 50 and older: averages and analysis of variance

Variables Origin groups
Total Asia Africa East Europe West Europe America FSU (after 1989) F df
Number of cases 930 156 213 279 74 34 175 –
Quality of life 2.8 2.8 2.9 2.9 3.1 3.0 2.5 14.7** 927
Life satisfaction 2.9 2.8 2.9 3.0 3.0 2.9 2.9 2.1+ 882
Depression 3.2 4.0 3.3 2.8 2.5 2.0 3.5 7.8** 928
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+

P < .10,

*

P < .05,

**

P <.01

Table 3 presents the bivariate correlations among all the study variables. As may be seen in the table, the majority of associations were significant and in the expected direction. Thus, for example, the three outcome measures were correlated with language proficiency and with most of the background variables. The variables “years since migration-YSM” and “age at migration”” were correlated with the quality of life measure. As can be seen, there is a very strong correlation between these two immigration variables (−0.85). Due to this high correlation, only one variable (YSM) was entered into the regression equations. In addition, it can be noted that most of the immigration and background variables were correlated with each other. Consequently, it was necessary to apply multivariate analysis in order to identify the strongest predictors.

Table 3.

Bivariate associations among the study variables: correlation matrix (N = 930)

Variables 1 2 3 4 5 6 7 8 9 10 11 12 13
1. Quality of life 1 .49** −.42** .23** −.30** .27** −.06 −.15** .15** .14** .26** .31** .36**
2. Life satisfaction 1 −.41** .03 −.04 .26** −.06 −.03 .12** .12** .19** .19** .36**
3. Depression 1 −.03 .10** −.33** .21** .14** −.16** −.22** −.18** −.20** −.43**
4. Years since migration 1 −.85** −.01 .00 .23** −.09** −.30** .15** .12** −.04
5. Age at migration 1 −.12** .30 .32** −.08* −.21** .18** −.17** −.07*
6. Language skills 1 −.06 −.26** .19** .31** .17** .19** .30**
7. Sex 1 .05 −.28** −.10** −.11** .01 −.04
8. Age 1 −.30** −.20** −.13** −.09** −.19**
9. Married 1 .13** .18** .04 .12**
10. Household income 1 .14** .15** .21**
11. Education 1 .09** .23**
12. Social activities 1 .19**
13. Health 1
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*

P < .05,

**

P <.01

The regression analyses were performed, as noted earlier, in three stages for each of the three outcome measures. In the first stage, the respective outcomes were regressed on origin group only. Western Europe served as the reference category. In the second stage, the outcomes were regressed on the two immigration variables1 in addition to origin group. In the final stage, the outcomes were regressed on origin, immigration and background variables. The results of the analyses appear in Table 4.

Table 4.

Predictors of quality of life, life satisfaction and depression among migrants to Israel: hierarchical regression analysis (beta coefficients)

Quality of life CASP
Life satisfaction LS
Depression euro-D
1 2 3 1 2 3 1 2 3
Origin
Asia −.15** −.11* −.02 −.13* −.09+ −.01 .18** .14** .07
Africa −.07 −.04 .05 −.06 −.03 .06 .11* .09+ .03
East Europe −.10* −.07 .01 −.01 .01 .06 .03 .03 −.03
America −.00 .01 .02 −.02 −.01 .00 −.05 −.05 −.06
FSU after 89 −.33** −.25** −.12+ −.05 .02 .07 .14** .17* .11
Immigration
Years since .08 .13* .07 .04 .05 .02
Language .27** .10** .25** .15** −.32** −.17**
Background
Gender −.00 −.02 .17**
Age −.03 .11** −.01
Married .07* .07* −.03
Income .09** .09** −.02
Education .07* −.00 −.05
Activities .18** .10** −.08**
Health .26** .29** −.33**
R2 .07 .15 .29 .01 .08 .19 .04 .14 .30
F value 14.4** 22.6** 26.8** 2.2** 10.1** 14.4** 6.8** 20.4** 27.2**
N 923 879 924
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+

Significance P < .10,

*

Significance P < .05,

**

Significance P < .01

Starting with quality of life, the first model shows that two origin groups—Asia and the Former Soviet Union (after 1989)—were associated with lower life quality, and East Europe was marginally associated. These associations weakened with the addition of the immigration variables into the regression procedure in the second stage, and all but disappeared when the background control variables were considered in the third stage. Only the Former Soviet Union retained a modest negative association. As for the other variables, the table shows that years since immigration and language proficiency were both positively associated with quality of life when the effect of the background variables was controlled. In addition, being married, higher income and education, greater social activity and better health were all associated with greater quality of life among the respondents in the sample.

Turning to the second well being measure, the table shows some similar trends. Origin group (Asia) was negatively associated with the life satisfaction measure in the first two stages of the analysis, but its effect disappeared in the final model. Language proficiency retained its positive association with life satisfaction even when the background variables were controlled, but the variable years since immigration was unrelated from the outset. Among the background variables, age, marital status, income, social activity and health were all associated with greater life satisfaction.

The third outcome measure was depressive symptoms. The results show that three origin groups (Asia, Africa and the Former Soviet Union) were positively associated with depressive symptoms even after controlling for the immigration variables. However, these associations disappeared when the background variables were taken into account. Language proficiency retained a negative association with the extent of reported depressive symptoms, but years since immigration was unrelated. As for the background variables, women had a greater tendency to report depressive symptoms. Healthier respondents and those who were more socially active, on the other hand, had a lesser tendency. The other background variables were unrelated.

Reviewing the results in relation to the hypotheses shows that they were only partially supported. As predicted, language proficiency was positively associated with quality of life and life satisfaction and negatively associated with depression (hypothesis 3). The same was true for the social capital measure (hypothesis 6). Economic status was associated in the posited direction with quality of life and life satisfaction, but not with depression (hypothesis 4). The remaining hypotheses received only limited support. Ethnic origin was associated only with the quality of life outcome and only among one group—immigrants from the Former Soviet Union after 1989 (hypothesis 1). Years since immigration showed a weak association with the quality of life outcome only, all else considered (hypothesis 2). And educational level was associated only with the quality of life measure (hypothesis 5).

4 Discussion

Consideration of the integration of immigrants by means of subjective parameters has not been sufficiently employed worldwide. It has also not received adequate attention in the Israeli context concerning the integration of elderly people who migrated during their lifetimes. The collection of data for the Israeli component of SHARE (the Survey of Health, Aging and Retirement in Europe) recently made analysis of this important area of inquiry possible. In order to better understand the factors that explain subjective well-being among the aging immigrant population in Israel, the current inquiry developed a conceptual model based upon the migration and social integration literature. The model presents a series of predictive variables that include: immigration variables, human capital, economic and social variables—all while controlling for demographic variables. The analyses were performed comparing immigrant groups who originated from six different areas of the world that have unique relevance for understanding the older Israeli immigrant population.

The descriptive results revealed significant differences between the six immigrant groups in all the independent variables, except for two demographic variables (gender and marital status). The groups significantly varied in the number of years in Israel and in the age upon arrival. Whereas immigrants originating in Europe, Asia and Africa arrived in Israel at the beginning of the 1950s, immigrants from America arrived during the 1960s, and immigrants from the Former Soviet Union came after 89 and are the least veteran in Israel. These findings are in congruence with the literature specified in our introduction (Amit and Semyonov 2006). The groups also significantly differed in their socio economic profile (income and education), as well as in their social capital and reported health status.

Prominent differences between the groups were also evident in two out of the three dependent variables, representing their post migration well-being: quality of life and depression. Older immigrants from the FSU reported the lowest level of life quality, and a significantly high level of depression in comparison to most other groups of the same age. Immigrants from Asia had higher depression rates and reported a low level of life quality. On the other hand, the groups did not vary significantly in their respective rankings on the third dependent variable—life satisfaction. As mentioned in the “Method” section, life satisfaction was measured by a single global indicator while the two other dependent variables, quality of life and depression, were measured by scales comprised of 12 items each. Although the use of a single item for measuring life satisfaction is generally acceptable (Bohnke 2008; Bonini 2008), Kahneman and Krueger (2006) recommend the use of multi-item indices. However, they recommend this only if the questionnaire items are defined in general terms. Future research that addresses this issue should take this suggestion into consideration.

The multivariate analysis in the current study, which was performed in three stages, revealed that the immigrants’ origin had no significant long term impact on their well-being after controlling for the effects of the immigration and background variables (economic, human and social capital). The only origin group that was associated with the well-being outcomes, and negatively so, was that of the FSU (after 89). For these immigrants, even after controlling for the background variables, an association was apparent between origin and their perceived quality of life and sense of depression. It should be reminded, that the FSU immigrant group is the largest recent immigrant group in Israel, and currently accounts for some 20% of the total Jewish population. As mentioned earlier, the FSU immigrants who arrived in Israel in mass numbers after the collapse of the Soviet Union in 1989 were led mainly by economic and political concerns (Rozenbaum-Tamari 2004). It is important also to note that FSU immigrants arrived in Israel with high levels of human capital relative to both the Soviet and the Israeli populations (e.g., Eckstein and Weiss 2002).

What explains their lower reported well-being? A recent analysis notes that many of the older immigrants from the FSU did not undertake gainful employment after their immigration to Israel (Litwin and Leshem 2009). More general studies of FSU immigrant economic assimilation in Israel have documented impressive employment levels among the immigrants, but this came partly at the cost of occupational downgrading compared with the occupations they held in their former country (Raijman and Semyonov 1997; Eckstein and Weiss 2002). Lack of occupational involvement and/or occupational downgrading might explain the lower levels of subjective sense of well-being reported among the FSU immigrants. However, recent studies also point to lower levels of life satisfaction among younger FSU immigrants (aged 20–60) in comparison with other highly skilled immigrant groups (Amit 2009). And, as was mentioned, earlier, it has been found that elderly FSU migrants report a lower level of life satisfaction than elderly veteran Israelis (Litwin 2005). In sum, the FSU immigrants constitute an interesting group that merits further research. Since immigrants from the FSU have also arrived at other destinations in the world (particularly Germany and the US) comparative research will help underscore whether the differences found in this analysis are mirrored in other settings as well.

The multivariate analysis employed in the current inquiry also reveals the importance of several predicting variables in relation to the well-being outcomes that were considered. As predicted in our third hypothesis, language proficiency was positively associated with quality of life and life satisfaction, and was negatively associated with depression. As mentioned, the language variable in the SHARE questionnaire did not directly address proficiency in the Hebrew (local) language, but rather asked about language proficiency per se. Clearly, a specific measure of local language proficiency is preferable in migration studies (Chiswick 2002). Nevertheless, we believe that most of the immigrant respondents interpreted the question to refer to proficiency in the Hebrew language. A study of the SHARE-Israel data by Ayalon found, in this regard, that new immigrants from the Former Soviet Union were significantly more likely than veteran Israeli Jews (including the native born) to rate their reading and writing abilities as impaired (Ayalon 2008). This was in spite of the fact that they had higher educational levels, on the whole. We recommend that future research specifically inquire about local language proficiency, in order to more firmly establish the contribution of this migration-related variable to well-being in late life among immigrants.

Among the background variables, reported health status and involvement in social activities were found to have had a significant impact on our three dependent variables in the regression model, indicating that the healthier individuals feel and the more socially active they are, the higher their subjective well-being is. In fact, health status was found to be the most significant predictor, a finding that is in congruence with findings from other studies on elderly people (Landau and Litwin 2001).

The positive association between involvement in social activities and well-being that is reported here has also been found in previous studies (Litwin 2005; Nilsson et al. 2006). However, when the studied population is comprised of immigrants, as is the case in the current inquiry, it is particularly interesting to distinguish whether these social activities occur mainly within the immigrant’s ethnic community or they take place with people from other ethnic groups. The social capital literature differentiates between bonding social capital, based on social networks within the ethnic group, and bridging social capital, which is based on social networks that cross ethnic boundaries. Bridging social capital would seem to be a better measure of social integration (Putnam 2000). Unfortunately, the variables available in the SHARE data set did not allow differentiation of these two types of social capital. Thus, it could be that the respondents’ social activities took place mainly within their ethnic communities and did not necessarily point to wider social integration. Nevertheless, their level of activity was positively associated with well-being.

Other background variables in the multivariate analysis predicted only part of the results in the dependent variables. As was anticipated in our fourth hypothesis, household income was positively associated with both quality of life and life satisfaction. This finding is congruent with findings from other studies which point to the importance of economic status in predicting an individual’s quality of life (e.g., Diener et al. 1993; Bohnke 2008). Contrary to our expectation, however, household income was not related to depressive state. In addition, it was found that married individuals reported higher levels of life quality and life satisfaction than unmarried did, but also that marital status was not related to depression. In contrast, gender significantly predicted depression but did not predict quality of life or life satisfaction.

In sum, the present study evaluated the integration of elderly people who had migrated to Israel at various points during their lifetimes. Successful integration was measured by means of several indices of subjective well-being. These measures included their perception of quality of life, their satisfaction with life and their emotional state. The findings show, for the most part, that ethnic origin is not a major predictor of successful integration in the long run. Except for among the most recent group of arrivals, the new immigrants from the Former Soviet Union, one’s region or continent of origin was unrelated to the well-being outcome measures when immigration variables, sociodemographic background, human and social capital and health factors were also taken into account. This suggests that over time, ethnic differences seem to matter less than other factors which shape opportunities and life chances. The study does point, however, to the importance of language proficiency as a means for the ultimate attainment of integration in the destination country. Thus, the path to a good old age among people who migrate in their lifetime includes at least one migration-related factor, above and beyond the factors that shape successful aging for all.

Footnotes

1

As mentioned, the correlation between YSM and age at migration was very strong (−0.85). We tried to enter these two variables into one equation, but the models did not fit. We then, examined each equation using one of the variables and the results were identical. Since YSM has more theoretical ground we decided to use it.

Contributor Information

Karin Amit, Email: karina@ruppin.ac.il, Ruppin Academic Center, Emek Hefer, Israel.

Howard Litwin, Email: mshowie@mscc.huji.ac.il, Hebrew University, Jerusalem, Israel.

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