Introduction

Subjective quality of life or subjective well-being (henceforward SWB) are emerging as important measures of individual and societal progress, as also envisaged by the 2030 Agenda for Sustainable Development (Fahey & Smyth, 2004; Bache, 2019; Kaminitz, 2020). Among the many individual factors associated with SWB (for an overview, see Paparusso, 2021), the quality of the neighbourhood is recently receiving growing attention as a factor shaping self-reported life satisfaction in contemporary societies. The quality of the neighbourhood is considered by the United Nations Sustainable Development Goal n. 3, which is aimed at ensuring “healthy lives and promote well-being for all at all ages”, and Goal n. 11, which advocates more efforts to “make cities and human settlements inclusive, safe, resilient and sustainable”.

Indeed, the place where people live may have a strong impact on their life patterns (e.g., school inclusion, labour market integration, civic participation, etc.), thus from a policy-making perspective it is necessary and relevant to make neighbourhoods more inclusive to ensure the well-being of people. Neighbourhoods should provide resilient human settlements, which drive sustainable development, stimulate innovation, and foster gender equality, community cohesion and personal safety among different population groups, including immigrants and their descendants.

According to the basic integration model, which can be defined as “the process of becoming an accepted part of the society” (Penninx & Garcés-Mascareñas, 2016), immigrants and their descendants look for the same qualities in a neighbourhood as do members of the mainstream population (Massey & Denton, 1985; Tran, 2020). Furthermore, this model recognizes that newly arriving immigrants may initially benefit from living in ethnoreligious enclaves, because they offer employment, and provide the comfort of being among their country of origin’s religious and cultural settings. Yet, across the integration path enclave residency switches from initially beneficial to becoming increasingly disadvantageous in terms of occupation and revenue (Andersson, 2021; Edin et al., 2003). In this perspective, migrants seek to live in a neighbourhood that is up to their attained socioeconomic status. Thus, the general neighbourhood characteristics can increase life satisfaction among immigrants and their descendants (Wiedner et al., 2022).

Previous research has showed that it is difficult to assess the quality of the neighbourhood only using objective or subjective measures. Most often a mix of objective measures is used together with subjective perceptions (Balducci & Checchi, 2009). However, in the real-world data, collection is often limited to either subjective or objective indicators of well-being, limiting the possibility of using the above-mentioned mix of indicators.

Based on a definition of Connerly and Marans (1985), for the perceived quality of the neighbourhood, we intend the subjective evaluation of the characteristics and services available in the immediate neighbourhood where people live (neighbourhood satisfaction), including the assessment of the local community and the frequency of social contacts outside the household but in the neighbourhood (attachment to the neighbourhood). However, to the best of our knowledge, studies focusing on the perceived quality of the neighbourhood are still scant and mainly developed in the US (e.g., Fernandez & Kulik, 1981; Connerly & Marans, 1985; Sirgy & Cornwell, 2002; Dittmann & Goebel, 2010; Cao, 2016; Varela et al., 2019; Hong & Park, 2021). Indeed, most of the studies on the neighbourhood focus on objective neighbourhood characteristics, such as the economic wealth, the residential density, the socio-economic status, the ethnic composition, the degree of segregation, affluence, or deprivation of the neighbourhood, etc. (e.g., Fleischmann et al., 2011; Frost et al., 2022; Pong & Hao, 2007; Wiedner et al., 2022; Wimark et al., 2019; Zeng & Zhang, 2022). A large majority of these studies examine the relationship of these indicators with other objective outcomes, such as education, labour market participation, occupational status, income, welfare support, health, residential mobility or attractiveness, attitudes towards immigrants, while only a few of them examine the relationship of these indicators with SWB.

Therefore, in this paper we aim to fill this gap in the SWB literature, comparing self-reported life satisfaction of different population groups (i.e., immigrants and natives) living in European countries, and to analyse the association between self-reported life satisfaction and the perceived quality of the neighbourhood, controlling for socio-demographic and human capital variables. Data stem from the cross-sectional European Quality of Life Survey (EQLS) of 2016, covering 28 European Union (EU) countries and five EU candidate countries: Albania, FYR Macedonia, Montenegro, Serbia, and Turkey.

The choice of using subjective indicators of quality of life and of the neighbourhood is justified by the following line of reasoning. As stressed by Veenhoven (2007: 16), “subjective indicators are indispensable in social policy, both for assessing policy success and for selecting policy goals. Objective indicators alone do not provide sufficient information, especially not on the subject of wellbeing”. As a consequence, the importance of objective indicators (both domain specific and overall indicators) has gradually left room to subjective measures of well-being (e.g., Pacheco et al., 2013). SWB measures are typically linked to a subjective evaluation, which comes by the individuals’ psychological and emotional sphere and can be affected by their personal attitudes (Alaimo et al., 2021), therefore there is need of data collection methods that ensure unbiased and accurate estimates (the so-called ‘non-sampling measurement error’). However, the main advantages of SWB measures, also for assessing the quality of the neighbourhood, are that they allow individuals to evaluate their own situation according to their personal criteria (Hendriks & Bartram, 2019). Subjective indicators of well-being capture perceptions and evaluations expressed by people themselves, as such they could be more appropriate than objective measures of outcomes to study individuals’ well-being (Hendriks & Bartram, 2019). Furthermore, individuals with similar levels of well-being as assessed by objective measures may report different outcomes in terms of subjective indicators of well-being (Grimes & Wesselbaum, 2021). Economic, cultural, and institutional factors, may affect these different outcomes. Therefore, indicators of subjective well-being could be an alternative and appropriate way to study individuals’ well-being (Hendriks & Bartram, 2019). However, it is well recognized that measures of subjective well-being may vary across individuals, and they are influenced by time and space for the same individual.

Consistently with this research strand, Kaiser and Oswald (2022) using longitudinal data from Australia, Germany and UK, have recently shown that subjective indicators of well-being (including those assessing neighbourhood satisfaction) “entered linearly in a regression performed fairly impressively when compared against a group of objective economic and social variables entered together in a regression”. Furthermore, research on neighbourhood features and life satisfaction have showed that neighbourhood satisfaction is a significant predictor of life satisfaction (e.g., Andrews & Withey, 2012; Barresi et al., 1984; Campbell et al., 1976; Sirgy et al., 2000).

Using subjective measures such as neighbourhood satisfaction does not come without limitation. Data are collected in surveys are often based on self-reports; therefore, they may be too noisy to offer any conclusion (Poon & Shang, 2014). However, according to social psychologists, aggregation over a large amount of people may ensure reliability of data based on individual scores characterized by a certain amount of noise (Di Tella & MacCulloch, 2006). A second limitation is also linked to measurement bias: respondents may have individual or group tendencies to give more positive or negative answers to subjective questions regarding both perceived quality of the neighbourhood and life satisfaction due to social desirability or other reasons (possible including cultural differences in receiving countries or immigrant groups), there would be a spurious relationship and the results obtained could suffer of an estimation bias.

However, few studies have so far addressed the well-being at fine geographical level. Indeed, studying the association between life satisfaction and a subjective measure of the quality of the neighbourhood may offer important insights for urban planning and community policy. Overall, there is a need to conduct more studies at the micro level based on subjective indicators (Wang & Wang, 2016).

The paper is structured as follows. “Theoretical Background and Study Hypothesis” section displays the theoretical background and our research hypotheses. “Data, Measures, and Method” section presents data, measures, and methods, followed by the results of our analysis in “Results” section. The last section reports the discussion and conclusions of our research.

Theoretical Background and Study Hypothesis

SWB and Migration

SWB has been defined by OECD (2013: 123) as “how people feel or how they assess their lives”. Looking at well-being from a subjective point of view, means conceptually converging towards ‘quality of life’. SWB consists in three components: life satisfaction, happiness (or hedonic well-being) and eudemonic well-being. Happiness is a concept which defines people’s emotional evaluation and measures their current feelings or moods, while life satisfaction is the (rational) cognitive dimension of well-being and it is a measure of people’s personal evaluation of their life as a whole (Diener et al., 1985). Lastly, eudemonic well-being is a concept which focuses on “judgments about the meaning and purpose of one’s life” (Steptoe et al., 2015: 641). Previous studies suggest some caution in using the concept of happiness, as it has a different meaning in different languages and cultures, it is more ephemeral and it depends directly on emotions, such as joy, anger, or distress (Carlquist et al., 2017). The concept of life satisfaction, in particular overall life satisfaction or one item satisfaction has the advantage to show strong reliability and less variability over time when repeatedly measured for the same person (Lutz et al., 2018). Therefore, in this paper, we have chosen to use self-reported life satisfaction as a measure of SWB.

In literature, there are four main approaches to study SWB and migration (Hendriks & Burger, 2021). The first one looks at how SWB affects migration decisions, conceived as both aspirations to leave and actual migration behaviours, in order to know if SWB is a driver of migration (e.g., Brzozowski & Coniglio, 2021; Schiele, 2021). The second one analyses how migration affects the SWB of migrants. More specifically it compares the SWB of migrants to that of non-migrants in the country of origin, to assess whether SWB increases after migration (e.g., de Haas, 2021; Steckermeier, 2021; Bartram, 2013; Amit & Riss, 2014; Stillman et al., 2015; Hendriks et al., 2018; Ivlevs et al., 2019; Hendriks, 2021). An emerging approach focuses on the impact of migration on the SWB of the hosting populations to understand how natives perceive migrants (e.g., Howley et al., 2020; O’Connor, 2020; Tatarko et al., 2021). Finally, the fourth approach looks at the differences in the SWB of migrants and natives and the main associated factors (e.g., Helliwell et al., 2018; Hendriks, 2015; Monteiro & Haan, 2022). This is one of the most difficult approaches, because of the scarcity of suitable data. However, this approach is important to verify if immigrants are satisfied as natives and to understand the reasons that could foster or hinder the achievement of a condition of parity with natives (e.g., Hendriks, 2015). Since for immigrants, the achievement of this condition could mean the realization of the integration process in the host society, this kind of comparison is particularly interesting and useful for effectively implementing inclusive integration policies (Hendriks & Birnberg, 2023). This is the approach that we will follow in this study.

Life Satisfaction Across European Countries and Population Groups

The focus of most of the studies on immigrants’ SWB is one national context. Because of the lack of surveys measuring immigrants’ SWB in European countries, few comparative studies on the SWB of immigrants living in European countries have been conducted so far. Furthermore, most of the available studies are based on the European Social Survey (ESS) which allows for comparisons between migrants and non-migrants and across immigrant generations (Arpino & de Valk, 2018).

All the studies realized so far in the European context have found that immigrants report lower SWB compared to natives. Even if those studies, as already stressed, are mainly based on ESS data, they differ not only in their aim, but most importantly in the choice of the control variables used. Safi (2010), and Kirmanoğlu and Başlevent (2014), relying on ESS data, showed that there is a gap between life satisfaction of immigrants living in Europe and natives, the former reporting lower levels of life satisfaction. Moreover, this gap, strongly affected by discrimination, continues even when considering the immigrant generation and the length of stay. Using data from the 2002–2003 wave of the ESS, Beier and Kroneberg (2013) found that symbolic boundaries have an impact on the life satisfaction of only first and second-generation immigrants with limited proficiency in the majority language.

Arpino and de Valk (2018) studied immigrants and natives in 34 European countries, taking also into account immigrants’ generation. Their findings show that first generation immigrants’ life satisfaction is lower compared to natives’ one, while the gap is reduced for second generation immigrants and 2.5 generation immigrants. However, in their study, no control for income is used, contrary to the other studies mentioned in this review. In the literature, it is largely acknowledged that income have a positive impact on SWB, thus omitting this important factor, may have brought different results compared to other studies. The study of Tegegne and Glanville (2019) is based on the data from the first five waves of the ESS. Their research suggests that reduced social capital is the main explanation to the lower level of SWB (constructed as the average of the happiness and life satisfaction variables) of immigrants in 15 European countries compared to their native-born counterparts. They also found a bigger gap in SWB between immigrants and natives. Their higher levels of social capital coming from religious involvement, are however not sufficient to compensate for the gap with natives.

Heizmann and Böhnke (2019), distinguishing between national citizens, EU citizens and third-country nationals (TCNs), found that only TCNs benefit from inclusive integration policies in terms of life satisfaction. EU immigrants are more affected by the negative impact of natives’ anti-immigrant attitudes. Using data from the 2010–2016 period of the ESS for 17 European countries, Hendriks and Burger (2020) showed that the development of less positive perceptions of the host country’s economic, political, and social conditions is associated with a reduction of first-generation immigrants’ SWB, although they have a SWB advantage compared to natives because of their more positive societal perceptions.

Finally, using data collected by the ESS from 2002 to 2018, Stranges et al. (2021) measured the relationship between immigrants’ self-reported life satisfaction and their absolute and relative income, the latter compared with that of natives and other immigrants with similar characteristics in the country of residence. They found a stronger association between immigrants’ life satisfaction and the absolute income than the relative income. However, life satisfaction is more strongly associated with income relative to natives than income relative to other immigrants. This is especially true for more educated immigrants who are more concerned in comparisons with reference groups. However, it is important to note that subjective measures of the own economic condition and the national socio-economic institutional condition moderate the relationship between relative income and SWB. By adopting the multi-level analysis, the study of Kogan et al. (2018) examined the national-level traits from three aspects: namely, the climate of immigrant reception, the extent of public goods provision and the level of economic inequality. Immigrants are likely to be more satisfied in countries that offer more welcoming social settings. However, this association is significant only when the social setting is measured by attitudes of the native-born towards immigrants, rather than by legal immigration regulations and policies. When considering the extent to which host country is able to provide public goods, country’s wealth levels seem not to matter for immigrants’ life satisfaction, whereas countries’ levels of human development is associated with an increase in immigrants’ life satisfaction. The role of economic inequality varies with immigrants’ own socio-economic statuses. On average, immigrants are less satisfied with their lives in host countries with higher levels of economic inequality. However, highly educated immigrants tend not to perceive economic inequality of the country as an obstacle of their satisfaction.

Life Satisfaction and the Perceived Quality of the Neighbourhood

In a pioneering study with data from the National Opinion Research Center’s Continuous National Survey in 1973–1974 (US), Fernandez and Kulik (1981) explored the effects of individual attributes, neighbourhood composition, and social comparison on self-reported life satisfaction. They first predicted an individual-level model using traditional variables that predict life satisfaction; then they considered neighbourhood context variables by including the percentage of neighbourhood residents who are white, the neighbourhood’s estimated cost of living, estimated income inequality within the neighbourhood and a dummy variable if the neighbourhood is urban. Among the individual-level predictors of life satisfaction, they found self-reported health status, age, education, and marital status. As far as the neighbourhood-context variables, they found that persons living in a neighbourhood with a high cost of living are less satisfied with their lives than those in low-cost neighbourhoods (holding family income constant, persons living in high-cost neighbourhoods are less affluent than those in low-cost areas) and persons living in cities are less satisfied than those living in rural areas.

Connerly and Marans (1985) explored the individual factors that are more likely to affect two global measures of perceived neighbourhood quality, satisfaction, and attachment, using data collected in the University of Michigan’s 1975 study of the quality of life in Detroit (US). They found that having nearby friends or relatives plays a significant role in both satisfaction and attachment. In particular, while the length of residence, age and having children are significantly associated with feeling attached to one’s neighbourhood, their impact on satisfaction is not significant. Specific neighbourhood attributes assume a dominant role in predicting satisfaction. Finally, the degree of how neighbours are like or unlike respondents is strongly associated with both attachment and satisfaction.

Using a mail survey among residents of Western Virginia (US), Sirgy and Cornwell (2002) tested how satisfaction with neighbourhood social, physical, and economic characteristics affect life satisfaction. They found that satisfaction with the neighbourhood’s social features contributes to community satisfaction, which in turn affects life satisfaction, while satisfaction with the neighbourhood’s physical and economic features affects life satisfaction through the mediating role of housing and home satisfaction.

Dittmann and Goebel (2010) studied the impact of socio-economic conditions and social integration into a local neighbourhood and life satisfaction in Germany, using the German Socio-Economic Panel (SOEP) study, enriched with data from the Micromarketing-System and Consult GmbH (microm) for the years 2000–2006. They showed that living in a neighbourhood with a higher socioeconomic status increases life satisfaction. Moreover, the individual gap between a person’s economic status and the status of the neighbourhood also affects life satisfaction: life satisfaction decreases when the person lives in a neighbourhood with a higher socio-economic status than his or her own, thus demonstrating the existence of an absolute and relative effect of neighbourhood status on life satisfaction. Finally, the availability of social networks has a strong positive effect on life satisfaction.

Using data from residents of five neighbourhoods in the Minneapolis-St. Paul metropolitan area (Twin cities in the US) in 2011, Cao (2016) studied the relationship between objective neighbourhood characteristics and life satisfaction, controlling for other socio-demographic factors. The author showed that high density and poor street connectivity negatively influence life satisfaction.

Varela et al. (2020) examined the effect of neighbourhood satisfaction, feeling safe at home and feeling safe in the neighbourhood on life satisfaction, controlling for age and gender, among 808 Chilean adolescents. Analyses showed that there is a direct effect of neighbourhood satisfaction, home safety, neighbourhood safety and age on life satisfaction. Moreover, home safety and neighbourhood safety have a direct effect on neighbourhood satisfaction. Finally, there is a positive indirect effect of feeling safe at home and feeling safe in the neighbourhood on life satisfaction.

Finally, Hong and Park (2021) analysed the spatial effects of social capital and urban characteristics on life satisfaction in 219 cities in South Korea, from the Korean Community Health Survey (KCHS) conducted in 2011, 2013, 2015, and 2017. The empirical results show that income, Gini-coefficient, social trust, social networks with friends, participation in charity activities, leisure activities, cultural facilities and availability of parks all affect life satisfaction in a positive way, except for Gini-coefficient, according to which an increase of income inequality harms life satisfaction.

Research Hypotheses

Based on the evidence described so far and the information available in the EQLS, we make the following hypotheses:

  • H1. First- and second-generation immigrants report lower life satisfaction compared to natives.

  • H2. A positive subjective evaluation of the characteristics and services available in the immediate neighbourhood where people live (neighbourhood satisfaction) is positively associated with life satisfaction.

  • H3. Direct contacts with friends, family members or relatives outside the household but in the immediate neighbourhood that are more frequent (attachment to the neighbourhood) are positively associated with self-reported life satisfaction, while indirect contacts are negatively associated with it.

  • H4. Country of residence matters for SWB. Socio-economic characteristics of the country of residence are associated with SWB.

Data, Measures, and Method

Data

Data stem from the European Quality of Life Survey (EQLS) of 2016, a unique pan-European survey. The survey deals with several issues, such as employment, income, education, housing, family, health, and work-life balance. It also looks at SWB topics, such as happiness, self-reported life satisfaction, satisfaction with the present state of the economy, satisfaction with the way democracy works in the respondent’s country of residence, satisfaction with the accommodation, satisfaction with the local area, satisfaction with the hospital or medical specialist services, self-perceived healthFootnote 1, etc. The sample consists of the adult population (aged 18 and plus) selected randomly for a face-to-face interview. The EQLS of 2016 includes 28 European Union (EU) Member states and five candidate countries: Albania, FYR Macedonia, Montenegro, Serbia, and Turkey. The final sample is composed of 30,205 individuals.

Measures

We have selected self-reported life satisfaction as the dependent variable. Self-reported life satisfaction was measured on a scale from 1 to 10. The question was: “All things considered, how satisfied would you say you are with your life these days? Please tell me on a scale of 1 to 10, where 1 means very dissatisfied and 10 means very satisfied.”

Based on previous findings, we selected the following independent variables. Socio-demographic variables: (1) gender (males (reference) and females), (2) age (in years), (3) age squared, (4) marital status (married, never married and widowed, separated, or divorced (reference)), (5) having children (yes (reference) and no); (6) place of residence (a city or a city suburb, a medium to large town, a village or small town and the open countryside (reference)), (7) migration background (G1 and G2and natives (reference)). Human capital variables: (8) educational attainment (primary education, secondary education, and tertiary education (reference)), (9) occupational condition (employed, other, retired, student and unemployed (reference)) and (10) income (in euros, PPP). Indicators of the perceived quality of the neighbourhood: (11) satisfaction with the accommodation (scale 1–10, from very 1 dissatisfied to 10 very satisfied), (12) a synthetic indicator of problems in the immediate neighbourhood of the respondent’s home such as noise, pollution, air quality, presence of garbage in the street, heavy traffic in the immediate neighbourhood measured with a dichotomic variable comparing those who reported having at least one major problem in the neighbourhood (coded as 0) with those who did not report any major problem in the neighbourhood (coded as 1). (13) feeling of safety at night in the neighbourhood (neither agree nor disagree, agree and disagree (reference)), (14) a synthetic indicator of availability of services in the immediate neighbourhood such as banking facilities, public transport facilities, cinema, theatres or cultural centres, recreational or green areas and, grocery shops or supermarkets measured with a dichotomic variable comparing those who reported to have at least one difficulty to access services in the neighbourhood (coded as 0) with those who did not report any difficulty to access services in the neighbourhood (coded as 1) (15) all people are treated equally in hospital and specialist medical services in my area (scale 1–10, from very 1 dissatisfied to 10 very satisfied), (16) frequency of direct contacts with family members or relatives living outside the household but in the immediate neighbourhood (scale 1–5, from 1 every day to 5 never), (17) frequency of direct contacts with friends living outside the household but in the immediate neighbourhood (scale 1–5, from 1 every day to 5 never), (18) frequency of indirect contacts (by phone, the Internet or by post) with family members or relatives living outside the household but in the immediate neighbourhood (scale 1–5, from 1 every day to 5 never) and (19) frequency of indirect contacts (by phone, the Internet or by post) with friends living outside the household but in the immediate neighbourhood (scale 1–5, from 1 every day to 5 never). Variables 10, 11 and 15 were also interacted with migration background.

Based on previous findings, as characteristics of the country of residence we chose three variables: unemployment rate, GDP per capita and life expectancy at birth. Data were retrieved for each country in the World Bank Database (World Bank 2023) for the year of survey (2016).

Method

As a first step, we carried out descriptive analyses. In order to study the association of observed variables on SWB at different levels (i.e. individual and country level), we implemented a series of two-level hierarchical linear regression models.Footnote 2 We have a total sample of 29,864 individual (level 1) and 33 countries (level 2).

Results

Descriptive Statistics

Our respondents show a quite high self-reported life satisfaction. As shown in Fig. 1, 12.9% of them score their life satisfaction at 5, while 11.4% have life satisfaction with a score of 6; 19.3% of the respondents report life satisfaction at level of 7, 23.3% of the sample feel satisfied with their life with a score of 8, 10.7% have a self-reported life satisfaction of 9 and 9.9% report a 10-level perceived satisfaction. The remaining 9.5% of respondents report a life satisfaction lower than 5.

Fig. 1
figure 1

Self-reported life satisfaction. Source: Authors’ elaboration of the EQLS, Pr > Ch2 < .0001

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Looking at our sample life satisfaction by migration background, we notice that the life satisfaction mean value is similar among natives (6.9, p < 0.0001), G1 (7.2, p < 0.0001) and G2 (7.1 p < 0.0001). However, looking at the per cent distribution among the scores, G2 have the highest percentage of scores 7 (23.4) and 8 (23.6), followed by G1, natives and G2, and finally, G1 has the highest percentage of score 10 (12.6) followed by G2. Among immigrant generations, self-reported life satisfaction has a higher variance compared to natives, and it is more concentrated in the scores ranging from 7 to 10 (Fig. 2).

Fig. 2
figure 2

Self-reported life satisfaction by migration background. Source: Authors’ elaboration of the EQLS Pr > Ch2 < .0001

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As for the independent variables (Table 1), our respondents average 49.6 years of age, with a preponderance of women (55.9%), married (54.1%), with children (63.5%), residing in a village or a small town (39.4%), native of the country of residence (84.2%). They have high educational attainment (62.4% secondary education and 28.4% tertiary education), they are predominantly employed (52.4%), and the average income is 1,309.5 euros in PPP.

Table 1 Descriptive statistics of covariates – N = 29,864
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As far as the perceived quality of the neighbourhood is concerned, respondents are quite satisfied with their accommodation (7.6 on average on a 10-point scale); half of them (52.7%) have reported at least one problem with noise pollution, air quality, presence of garbage in the street, heavy traffic, while they are neutral to the feeling of safety in the neighbourhood (71%). The respondents feel to be treated equally in hospital in their area (7.1 on average on a 10-point scale); they find that the services offered in their neighbourhood are quite good (48.4% reported rather or very easy access) when it comes to the availability of bank facilities, public transport facilities, cinema, theatres, recreational facilities and green areas, and grocery and supermarkets shops. Lastly, the respondents have regular direct and indirect (by phone, Internet or by post) with family members and friends living in the same neighbourhood (respectively 1.9 and 1.8 on average on a 5-point scale ranging from every day to never) and with family members and friends living in the neighbourhood (respectively 1.9 and 2.1 on average on a 5-point scale ranging from every day to never).

Country levels variables used have respectively the following mean values for the 33 countries included in the survey: unemployment rate 9.7%, GDP per capita (in PPP US dollars) 28,829 and life expectancy at birth 79.7 years.

Regression Results

Tables 2 and 3 show the results of the hierarchical linear regression model.

Table 2 Effects of individual-level predictors on life satisfaction and variance components
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Table 3 Effects of individual-level predictors on life satisfaction and variance components with interactions and coefficients for macro-level predicting life satisfaction and respective variance components
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In Model 0, we first include only the intercept. We then add the individual level characteristics in the Models 1 to 4. In Model 5 we included a full set of variables at both the country and individual level. The results of Models 1–3 are presented in Table 2 together with random effects (variance components), while in Table 3 are presented the results of Models 4–5. Model 0 is the null model used to calculate the Intra Class Correlation (ICC) and provides information on how much variation in the outcome exists between level-2 units. The results of the model confirm the need to use a hierarchical strategy. Model 1 includes only the migration background in order to provide the baseline average in SWB between natives and immigrants (first- and second-generation) across European countries. The results show that both first- and second-generation migrants have lower SWB compared to natives. However, only the results for first-generation migrants are weakly statistically significative. In Model 2, we control for socio-demographic and human capital variables.

As far as the demographic variables are concerned, women are more satisfied with life than men. Age is negatively associated with life satisfaction: the higher the age, the lower is the level of self-reported life satisfaction. However, the age squared is positive, this means that the relationship between age and life satisfaction is not linear and the negative association between life satisfaction and age is reduced as individuals get older. Having children is positively associated with life satisfaction. Living in urban areas, irrespectively of the dimension of the city or the town, is negatively associated with self-reported life satisfaction, compared to living in the countryside. First and second-generation immigrants are less satisfied with life compared to natives. Compared to Model 1 the gap with natives in SWB is reduced and it is significant only for first generation migrants.

Concerning the human capital factors, as expected people with primary and secondary education exhibit lower levels of life satisfaction than those with tertiary education. Moreover, those who are students and employed show the highest levels of life satisfaction. Finally, individual with at higher income levels, correspond higher levels of SWB.

In Model 3 we added the variables related to the perceived quality of the neighbourhood. Having at least one problem with the noise, pollution, air quality, presence of garbage in the street and heavy traffic in the immediate neighbourhood is negatively associated with self-reported life satisfaction. On the contrary, feeling safe at night in the neighbourhood is positively associated with life satisfaction. Similarly, the availability of public transport facilities, cinemas, theatres, cultural centres, and recreational or green areas is positively associated with self-reported life satisfaction. Finally, having less frequent direct face-to-face contacts with friends outside the household but in the immediate neighbourhood is negatively associated with self-reported life satisfaction; having less frequent indirect contacts (by phone, the Internet or by post) with any family members or relatives is positively associated with self-reported life satisfaction; and having less frequent indirect contacts with friends is negatively associated with satisfaction with life. First and second-generation immigrants are less satisfied with life compared to natives. Compared to Model 1 and 2 the gap with natives in SWB is reduced however it is not significant for both for first- and second- generation migrants.

Overall, hierarchical regression results show that the socio-demographic variables, the human capital factors, and the indicators of the perceived quality of the neighbourhood are all important in explaining self-reported life satisfaction among immigrants and natives in European countries.

In Model 4 we add to Model 3 an interaction of the variable migration background with income, satisfaction with accommodation and feeling that all people are treated equally in hospital and specialist medical services in the neighbourhood. The results show a negative relation by migration background compared to natives, however in this Model migration background shows a positive relation with SWB compared to natives (significant for second-generation migrants). Those findings reveal a stronger association of the living conditions, thus of the socio-economic integration, with the life satisfaction of immigrants, compared to natives.

As final model we run Model 5 where we introduce 3 variables as proxy of the socio-economic conditions at the country level. The three variables are significant and go in the expected direction. More specifically the higher the unemployment level in the country, the lower the SWB; the higher the GDP per capita and the life expectancy, the higher the SWB.

Discussion and Conclusions

The topics of SWB and happiness are becoming increasingly popular among scholars, researchers, and policymakers. They are perceived as important as GDP and other macroeconomic indicators in evaluating the well-being of individuals and countries. In particular, self-reported life satisfaction refers to how people judge their life as a whole; therefore, it is a rational evaluation of one’s situation according to personal criteria. Since it contains a cognitive evaluation of people’s current needs and future expectations, it is considered particularly useful to estimate the quality of life within a country or a social group.

Recently the quality of the neighbourhood, both objectively and subjectively measured, is capturing growing attention as a factor shaping individuals’ SWB, as also envisaged by the 2030 Agenda for Sustainable Development. However, to the best of our knowledge, studies measuring the relationship between life satisfaction and the perceived quality of the neighbourhood in the European context are still very few. In this paper, we aimed to fill this gap in the literature, analysing the association between self-reported life satisfaction and several indicators of the perceived quality of the neighbourhood, controlling for other socio-demographic and human capital variables and the socio-economic characteristics of the country of residence among immigrants and natives in Europe. Data stem from the cross-sectional European Quality of Life Survey (EQLS) of 2016. In particular, we tested four research hypotheses.

Our results are mixed: in the first three models, first- and second-generation immigrants have lower level of self-reported life satisfaction compared to native. However, differently from most previous studies (e.g., Arpino & de Valk, 2018; Kirmanoğlu & Başlevent, 2014; Tegegne & Glanville, 2019), when interaction with income and quality of the neighbourhood factors are introduced, we found that first and second generation immigrants report higher self-reported life satisfaction compared to natives (H1). In particular, those belonging to the second generation are the most satisfied with life, as also found by Giovanis (2021). However, this finding is mediated by other variables that are more linked to immigrants’ socio-economic integration in the country of residence, such as income, satisfaction with the accommodation and perceived discrimination in the provision of health services. Such results confirm that immigrants are more disadvantaged compared to natives in terms of living conditions and access to services (Monteiro & Haan, 2022).

Second, our findings show that the positive subjective evaluation of the characteristics and services available in the immediate neighbourhood where people live (neighbourhood satisfaction) is positively associated with self-reported life satisfaction (H2). Previous research has shown that there is a positive relationship between neighbourhood characteristics and life satisfaction (e.g., Hong & Park, 2021; Varela et al., 2019). In particular, as reported by Giovanis (2021), the availability of socio-cultural and recreational activities in the neighbourhood increases the life satisfaction of both natives and immigrants, suggesting the importance of the quality of the neighbourhood for the socio-cultural integration and, in policy terms, for the creation of inclusive, secure, and happier communities.

Third, as far as the attachment to the neighbourhood is concerned, having less frequent direct face-to-face contacts with friends or neighbours is positively associated with life satisfaction. Having less frequent contacts with any family members or relatives by phone, on the Internet or by post is positively associated with life satisfaction. Having less frequent contacts with friends or neighbours by phone, on the Internet or by post is negatively associated with life satisfaction. Therefore, it seems that is less important to have indirect contact with family members, while with friends the opposite is true (H3). Previous research (e.g., Connerly & Marans, 1985; Dittmann & Goebel, 2010) has shown the positive relationship between contacts and social networks in the neighbourhood and life satisfaction. For instance, the attachment to the neighbourhood is a factor increasing life satisfaction and therefore a reason for continuing to live in the same place of residence, instead of moving to another neighbourhood (Casakin et al., 2021).

Finally, the characteristics of the country of residence matter for both native and immigrants’ life satisfaction (H4). Immigrants are more satisfied in countries with higher quality of life captured by country GDP per capita, life expectancy and unemployment rate.

The paper has provided evidence to support the notion that the perceived quality of the neighbourhood, and the interrelated factors, can have positive results in terms of life satisfaction. There is also evidence of immigrants-natives differentials, which are essentially due to integration gaps. This highlights the need for targeted rather than broad policy interventions to maximise the positive contribution of the main factors associated with life satisfaction. Since the integration process takes place primarily at the local level (Penninx et al., 2004), with cities and municipalities as the places where immigrants are received – find a home and a job, have children and access to health facilities – and natives encounter new cultures and identities, we believe that improving the quality of the neighbourhood characteristics and facilitating social networks and sense of attachment is beneficial of the well-being of both immigrants and natives.

However, there are some limitations to the study, which must be recognized. First, this study is based on a cross-sectional survey. This means that the situation at the date of observation alone is analysed, therefore, the effect of specific life course events on life satisfaction can be only evaluated retrospectively. Moreover, we cannot exclude reverse causality between the variables studied, given the cross-sectional structure of the data. For instance, we cannot establish the direction of the relationship between income and life satisfaction. In other words, we do not know if income increases life satisfaction or if people with a higher life satisfaction are more likely to achieve a higher income. The use of longitudinal data could help to shed light on the causality between variables. However, although much progress has been done, longitudinal data are still scant or not entirely suitable for the examination of changes in SWB. Third, information such as the causes of migration, the country of origin, the ethnic composition, the ethnic density and the socio-economic status of the neighbourhood are not available in the EQLS, therefore we could not assess the association of those variables with life satisfaction. Finally, the neighbourhood support and a sense of community are indicators that are positively associated with life satisfaction (e.g., Novara et al., 2023; Sheng et al., 2019); however, the EQLS do not provide this information.

Cultural constructions of selfhood (i.e. individual self; interconnected self; relational self, etc.) as well as values, norms, self-centred, or distally-centred prioritization of the pursuit of wellbeing, etc., all vary widely across different cultures among immigrants and refugees. Generic solutions for generic people have little practical meaning and value beyond theoretical framings. A useful next step would be to pursue a translational study investigating such cultural variables that could produce findings to inform targeted policy changes. Moreover, exploring methods to promote multicultural awareness in schools, through social media, and internet platforms, to educate the public and relevant stakeholders about the importance of reducing discrimination towards immigrants may be crucial. We also believe that encouraging immigrants to participate in public hearings and voice their concerns and dissatisfactions to the authorities can foster inclusiveness and ensure that the perspectives of immigrants are considered in policymaking and community development.