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Subjective well-being in rural and urban Italy
Comparing two survey waves (2008–2018)

Individual well-being is a multidimensional concept based on physical and psychological dimensions. As far as psychological well-being is concerned, there are several factors affecting its value, including income, age, gender, education, civic status and employment. One of the most interesting variables which has been considered in the literature is related to the place of residence, differentiating the urban and rural settings. The purpose of this population-based country study is to examine the association between subjective individual well-being and urban and rural areas in Italy, comparing the data of two survey waves (run in 2008 and 2018) in a statistically significant sample of 1,500 citizens among the Italian population. At a general level, in ten years some variables have changed, but if in 2008 the score for perceived well-being was higher in the rural context, in 2018 results show a similar level of subjective well-being among rural and urban dwellers. The results reveal even more interesting aspects when one looks at the variation of the determinants of well-being in the two areas, showing that some immaterial aspects, such as social relations and cultural life, become relevant determinants of subjective well-being for both contexts, independently from the differences in the cultural and social supply in the rural and the urban life.

Introduction

Since the early 2000s, many disciplines have begun to examine urban and rural differences and to investigate the relationship between well-being and the degree of urbanisation of the place where individuals live. From sociologists to economists, from urban planners to psychologists and medical researchers, all are providing evidence on how well-being is determined by different factors and how well-being varies across countries.

The purpose of this chapter, which is a population-based country study based on two survey waves (2008 and 2018), is to examine how individual subjective well-being may have changed over ten years in the urban and rural contexts in Italy. Building on the results of the first survey wave (2008), the most prominent result of which was a better score of the general perception of well-being for the rural dwellers (Viganò et al., 2019), which was partially consistent with similar results at European and extra-European level, we wished to answer the following research questions: first, what are the most significant determinants of well-being in the two areas, and second, whether significant changes have occurred both in absolute terms (change in perception of well-being) and in more specific terms, i.e. considering the variability of the variables over ten years.

The chapter develops as follows: in the first section we report the main literature evidence on the key topics related to differences in urban and rural well-being; the second section introduces the methodology adopted and clarifies the survey results in a comparative perspective; the third section analyses and discusses the survey data; and the final section presents conclusions.

Differences in rural and urban well-being and well-being determinants

The literature on well-being in urban and rural areas is articulated around three main positions, all of which are supported by empirical studies: urban researchers, championed by the work of Glaeser (2011), report the major benefits of city life, iconised by the agglomeration effect and the prevailing industrial growth scheme (higher economic production, a more dynamic labour market and consequently more job opportunities, higher salaries, higher rate of innovation and creativity and more access to goods and services of various types, e.g. institutional, educational, financial and cultural) (Fujita & Thisse, 1996; Morrison, 2011; Glaeser, 2011; Morris, 2019). The negative counterparts of living in an urban setting are well-known and decried under the wording ‘urban malaise’ (Wirth, 1938; Okulicz-Kozaryn & Mazelis, 2018; Mouratidis, 2019; Okulicz-Kozaryn & Valente, 2020): the increase in inequalities (higher costs of living and new forms of poverty) and social exclusion, and the diverse impacts on the environment (e.g. negative externalities in terms of pollution, environmental legacy and a denser and more crowded environment).

On the other hand, the ‘ruralists’ highlight how life in a less urbanised context can have several positive effects, while taking into account certain limitations related to the provision of services, job opportunities, culture, etc. in rural areas (Glendinning et al., 2003; Knight & Gunatilaka, 2010; Brereton et al., 2011; Sørensen, 2014; Okulicz-Kozaryn, 2015). Among the most relevant arguments in favour of rural areas is the relationship with the environment in relation to quality of life. The quality and quantity of the environment, along with the interactions between humans and the natural, anthropic spaces, are fundamental to the perception of quality of life and well-being (Hegetschweiler et al., 2017). In this perspective, there is strong evidence of the positive effect of living close to the natural environment, green areas, parks and the general ecosystem which speaks in favour of living in rural areas rather than in urban (Van den Berg et al., 2003; Lawson, 2009; Berman et al., 2008, 2012; Maller et al., 2006; Wheeler et al., 2012; White et al., 2013).

Additionally, a number of studies showed that there is no significant difference between subjective well-being in rural and urban areas (Burger et al., 2020; Sørensen, 2014; Berry & Okulicz-Kozaryn, 2011). Among the determinants of well-being in relation to urban–rural area as place of residence that have been considered by scholars, without necessarily placing the contributions within the three positions mentioned above, the following should therefore be considered. Among the factors affecting individual psychological well-being in relation to the conurbation of the anthropic space, it is worth mentioning the quality of housing (Evans, 2003), the concentration of physical infrastructure (Barton, 2009; Mouratidis, 2019), the infrastructural density in relation to the rate of criminality (Mendez & Otero, 2018) and the lack of spaces for interaction and recreation (Boyko & Cooper, 2011). With regard to this last aspect, it is observed that the deficit of socio-spatial spaces encourages poor behaviour and perceptions in people living in high-density spaces, with reduced cognitive and social functioning (Gifford, 2007; Mouratidis, 2019). In this respect the living conditions of rural dwellers appear superior since they inhabit a less crowded and stressful environment (Gilbert et al., 2016).

Another relevant dimension which has been widely investigated in the literature on social capital is social and community engagement. Starting with the seminal work of Putnam (2000; Putnam et al., 1993), networks, norms and trust are highlighted as the main relevant factors for the social and economic growth of communities. As noted by Portela et al. (2013), the quantity of social capital may increase the perception of individual well-being, given the satisfaction deriving from the social engagement opportunities with others and the perception of being locally connected to the social context.

Following on from the initial hypothesis of higher social capital in rural areas suggested by Putnam (2000; Putnam et al., 1993), the presence of social capital, articulated in different ways in urban and rural areas, becomes an important factor to be taken into account (Hofferth & Iceland, 1998; Beugelsdijk & Van Schaik, 2005; Léon, 2005; Sørensen, 2012, 2014, 2016). A positive perception of place is linked to the economic and social opportunities provided by the environment, but also to the sense of inclusion within a community, which corresponds to a more cohesive social capital (Berry & Okulicz-Kozaryn, 2011; Morrison, 2011; Ballas & Tranmer, 2012; Okulicz-Kozaryn, 2015; Rishbeth et al., 2019). The proxy that some standard studies have used to measure social capital is participation in associations and voluntary activities (Putnam et al., 1993; Sørensen, 2012) as a measure of trust. Community engagement is also signalled as a counterbalance to offset the isolation effect in the rural context (Hofferth & Iceland, 1998; Ziersch et al., 2009).

Additional elements which may affect subjective well-being are related to cultural and sports activities. Several studies have highlighted the influence of these elements as well-being determinants, like the propensity towards attending exhibitions or playing an instrument, or the tendency to practice sports (Glaeser et al., 2001; Michalos & Kahlke, 2008; Easterlin et al., 2011; Grossi et al., 2012). In this respect, it emerges that cultural experience seems to have a noticeable impact on individuals, and the intensity of participation and consumption is significantly correlated to the subjective perception of well-being, highlighting culture as one of the main determinants, after health status and income.

Practicing sports has also become one of the main supports in relation to the development of health policies in Western countries over the last thirty years, given the opportunity to prevent health problems and reduce costs for the health system. Sports participation has been demonstrated to have a positive effect upon individual well-being (Downward & Rasciute, 2011) and the effect increases if the activity chosen is shared with others, which in addition allows social interaction (Cleland et al., 2015).

When thinking of the provision of cultural and sports activities, the urban areas and the conurbation display a higher concentration of supplies like shops, sports facilities, cultural facilities, museums etc. (Insch & Florek, 2010; Zenker et al., 2013; Tavano Blessi et al., 2016).

The size of conurbation and the dimension of the living place have recently been investigated in empirical studies showing how satisfaction or dissatisfaction can be variously related to the size of cities, towns or villages. Numerous studies show greater dissatisfaction linked to city life, as already reported (Berry & Okulicz-Kozaryn, 2011; Okulicz-Kozaryn & Mazelis, 2018; Mouratidis, 2019; Okulicz-Kozaryn & Valente, 2020), according to the size of conurbation, while in smaller settlements, villages or small towns people seem to be more satisfied (Ballas & Tranmer, 2012; Requena, 2016; Viganò et al., 2019; Burger et al., 2020).

Methods

The analysis is based on two survey waves carried out in 2008 and 2018, both conducted on a sample of 1,500 citizens selected to be representative of the Italian population. In order to analyse and evaluate the determinants of the subjective well-being in the two environments, the two surveys were based on the same questionnaire, addressed to a statistically representative sample of Italian residents equally distributed in the urban and rural areas. The survey was based on the PGWBI (Psychological General Wellbeing Index) questionnaire,1 an instrument targeted specifically at measuring individual subjective well-being and used for the evaluation of the impact of different determinants.

The questionnaire collected a sample of the main socio-demographic characteristics such as gender, age, education, income, diseases, employment and civil status (Table 19.1). In line with what has emerged in the literature about the determinants of well-being, four indexes (or composite indicators) were identified for this study, with the purpose of showing their variation in the different territorial contexts, also taking into account the dimension of the living environment.

Each index has been calculated through the aggregation of the results of specific sub-questions:

  • Cultural Index: Fifteen questions related to participation in cultural activities such as theatre, museums, exhibitions, cinema, reading a book, music etc. in terms of frequency per year in a scale from 0 to 365 (the value of the index is given by the sum of the results).
  • Health Index: the presence (1) or absence (0) of selected diseases as listed in the PGWBI questionnaire.
  • Social Index: Two questions related to participation in social and community activity and engagement in volunteer organisations in terms of frequency per year on a scale from 0 to 365 (the value of the index is given by the sum of the results).
  • Sports Index: Two questions related to the intensity of practicing sports and physical activity in terms of frequency per years on a scale from 0 to 365 (the value of the index is given by the sum of the results).

We have employed linear statistical techniques related to univariate analysis (Pearson’s) in order to describe the difference in terms of impact on individual subjective well-being. In relation to it, we underline that the difference is not reported in terms of effect size, but refers to the incidence that each determinant analysed may provide in relation to the well-being perception. Table 19.1 provides the whole sample characteristics compared to the general Italian population for the national survey in 2011 and 2018.

2008 Survey wave N % % Italian population (Istat, 2011) 2018 Survey wave N % % Italian population (Istat, 2018)
GENDER
Male
Female
726
779
48
52
48
52
GENDER
Male
Female
727
777
48
52
48.7
51.3
AGE GROUPS
• 15–17
• 18–34
• 35–54
• 55 +
53
397
507
548
3.5
26.4
33.7
36.4
3.5
24.2
35.0
37.3
AGE GROUPS
• 15–17
• 18–34
• 35–54
• 55 +
20
250
559
675
1.3
16.6
37.1
44.8
3.8
19.2
29.6
36.6
LOCATION
North
Centre
South
690
295
520
45.8
19.6
34.6
45.8
19.8
34.4
LOCATION
North
Centre
South
724
293
481
48.1
19.4
31.9
46.3
19.7
33.7

In order to define the urban and rural scale and to ring-fence the sample (Table 19.2), we have taken two different methodological steps: first, we have employed administrative data (Istat census) to locate the respondents (objective number of inhabitants per urbanisation level); second, acting on the suggestion of Sørensen (2012), we have defined four cut-offs (settlements with fewer than 5,000; 5,001–20,000; 20,001–100,000; more than 100,000); and then defined four categories of human settlements: rural, semi-rural, semi-urban and urban areas. Table 19.2 provides evidence on the number of rural and urban dwellers considered in the sample.

2008 <5,000 (rural) 2008 >100,000 (urban) 2018 <5,000 (rural) 2018 >100,000 (urban)
276 329 270 337

For the present study, in order to focus more sharply on rural and urban contexts, we have concentrated our analysis on the two greatly contrasting territorial areas, employing linear statistical techniques. Table 19.3 presents the results of the linear correlation coefficients between the selected variables and the four indexes.

2008 2018
Rural Urban Rural Urban
N 276 329 270 337
social indicator –0.067 0.008 0.138* 0.102
cultural indicator 0.047 –0.01 0.105 0.155*
sports indicator 0.219* 0.086 0.26* 0.172*
health indicator –0.267* –0.174* –0.252* –0.23*
female –0.179* –0.071 –0.19* –0.215*
male 0.179* 0.071 0.19* 0.215*
single 0.093 –0.023 –0.071 –0.052
married –0.097 0.003 0.028 0.089
divorced –0.014 0.101 0.118 –0.014
widowed 0.025 –0.032 –0.046 –0.002
student 0.021 0.008 0.034 –0.086
blue collar –0.06 0.111* –0.131* –0.044
white collar 0.096 –0.119* 0.092 –0.025
retired –0.022 0.053 0.018 0.102
income nd** –0.064 –0.017 0.074 –0.076
income low –0.039 0.013 0.016 –0.083
income average 0.056 0.081 –0.045 0.101
income high 0.112 –0.059 0.024 –0.038
North-West –0.07 0.105 0.078 –0.039
North-East 0.126* 0.062 0.008 0.184*
Centre 0.006 –0.085 0.07 0.066
South and islands –0.071 –0.072 –0.9 –0.13*

*Statistically significant results

**data not available

Data analysis

The results presented come from the comparison of the correlation index obtained from the variables (Table 19.3) in the two waves (2008 and 2018). The four indexes and the main socio-demographic variables selected (gender, civil status, income, work typology and geography (Table 19.3) have been correlated to PGWBI through a linear correlation analysis, which allows us to outline the urban–rural differences and the different scoring of the variables in the two contexts.

The results of our analysis in the 2008 wave showed a better scoring of the general level of PGWBI in the rural context (with an interesting implication concerning the size of urban settlement in favour of small towns or villages with fewer than 5,000 inhabitants), reporting an average value of 79.353 for the rural areas and 77.516 for the urban (Viganò et al., 2019).

Ten years later (2018), the average value had changed by a small number of points, but the results are reversed: the rural average PGWBI is 77.823, while the urban is slightly increased, reaching the value of 78.560.

Although the result shows a slight decline in perceived well-being in rural areas and a slight improvement in urban areas, bringing the results of the most recent wave in line with studies proving little or no difference between urban and rural areas, what is more interesting is to observe which variables have had a different impact over ten years and what dynamics are emerging in the different contexts.

One of the most noticeable changes concerns social dynamics, signalled by the social index. As far as the social dimension is concerned, identified in the literature as social capital and captured in our analysis through two questions related to social involvement of individuals in voluntary and community development activities, in 2008 this index was negative (–0.067), but in ten years it became a significant factor (0.138, statistically significant), proving even stronger than the urban average value.

The results of the 2018 social index are aligned with the position of some scholars who claim ‘smaller is better’. Voluntary work and associations, considered a proxy of social capital (Putnam, 2000; Sørensen, 2012), are increasing the level of well-being and strengthening trust and collaboration among the community’s members (Glaeser et al., 2001; Uslaner, 2008).

Another relevant change concerns the results of th e cultural index. The cultural dimension, investigated through a set of questions concerning the individual consumption of and participation in cultural initiatives, is listed in the literature as a relevant aspect in promoting individual well-being (Grossi et al., 2012; Hyyppä et al., 2006; Michalos & Kahlke, 2008; Tavano Blessi et al., 2016). From 2008 to 2018 the cultural index went from being a minor factor for well-being to becoming an element of proven relevance, meaning an increase in well-being linked to the consumption of recreational and cultural supply. The results appear statistically significant in urban areas in 2018, but culture counts as a determining variable for PGWBI also for the rural dwellers, who prove to be cultural consumers, regardless of the local availability of cultural supply.

The sports index, obtained by self-reported frequency of practicing physical/sports activities over one year, measured here on a scale from 0 to 365, is considerably higher in rural areas (0.219 in 2008 and 0.26 in 2018), with an increase in the value of urban areas over the ten years. The literature shows that physical activity and access to nature are sources of physical and psychological well-being, and have a protective effect against diseases (Berman et al., 2008, 2012; Maller et al., 2006; White et al., 2013). The higher results in rural contexts can easily be explained by the presence of accessible green spaces and natural parks, which counterbalance less provision of sports and physical infrastructure (Stigsdotter et al., 2010).

As far as the health index is concerned, the strongest determinant of individual psychological well-being is the presence or absence of disease. In our analysis, the health index is given by the number of declared diseases, as sought in the PGWBI questionnaire. The results over ten years have increased in urban settings, meaning a worsening or a higher negative incidence of this variable on well-being. It might be observed that both rural and urban dwellers in the two waves present co-morbidity and a negative correlation with individual subjective well-being. The literature in this regard has highlighted the bilateral influence of positive well-being on individual health (Diener & Chan, 2011) and, conversely, how health condition and co-morbidity affect subjective well-being. In the two waves, results prove the relevance of this variable in both urban and rural contexts (in all the contexts and all the years considered the variable is statistically significant), despite the higher density of welfare and health infrastructure in the urban areas (McDonald et al., 2014). The Italian National Health System providing health services to the whole population can partially explain why the results do not present significant divergences.

2008 (rural) 2008 (urban) 2018 (rural) 2018 (urban)
79,353 77,516 77,823 78,560

Coming to single variables, it is worth considering the persistence and worsening of the gender gap in favour of men in both contexts. It should be observed that the female condition presents a strong negative correlation with the urban area, reversing the results of 2008, in which it was assumed the presence of better urban welfare services for the work–life balance of women.

Civil status is always difficult to interpret as the data over ten years present some small changes. None of the results are statistically significant, but we can observe that being single in a rural area steadily changed in ten years and worsened a little, while the condition of being married or divorced in rural areas seems to provide a positive effect in terms of well-being. In the urban area, the only value which strengthens the negative correlation with well-being seems to be being divorced. Being a student in an urban setting also leads to a negative correlation with well-being (in 2018).

Another relevant correlated factor of well-being is economic condition or income (Chu-Liang, 2009). Previous results reported greater hardship for low-income earners and higher advantage for high-income dwellers in rural areas, probably because of job type (clustered into the two main categories of white and blue collar). Over the ten years, considering the long shadow cast by the 2008 crisis, the perception of well-being worsened for low-income urban dwellers and improved for their rural counterparts, while it is significant to note that workers with average salaries (intermediate stage between white and blue collar such as manager or industry-employed workers) reported better well-being in urban areas.

A final point concerns the geographical distribution of well-being across regions which report a historical Italian divide between the northern part of Italy (which scores better for all the dimensions and the territorial contexts) and the rest of Italy. Over ten years this situation was confirmed as far as southern Italy and the islands are concerned, while in central Italy urban areas are steadily improving their score.

Conclusion

In this chapter, we have compared statistical data from two waves (2008 and 2018) concerning the perception of individual psychological well-being in rural and urban Italy. Population (number of inhabitants per scale of urbanisation) has been the objective criterion for classifying the clusters in our country study. The rationale for employing a cut-off scale has been the adaptation to the size of Italian towns and cities, the majority of which have fewer than 100,000 inhabitants. To make a more clear-cut choice for this chapter, we have selected the results of those rural areas corresponding to settlements with fewer than 5,000 inhabitants and the urban areas with more than 100,000 inhabitants.

Furthermore, our analysis has considered how the set of socio-demographic variables, together with the four indexes (social, cultural, health and sports index), might affect subjective well-being in the different environments.

The results of our comparative analysis show that in ten years the trend in perceived well-being, calculated in relation to the indices, the socio-demographic variables and the PGWBI, tends to rebalance between urban and rural areas, after a better performance in rural areas in 2008.

However, some factors have changed significantly, highlighting which features of well-being become most relevant: while the health and sports indexes confirm their relevance in both contexts, the social and cultural indexes are on the rise, specifically in the rural areas, phenomena that argue in favour of a value per se of these elements, notwithstanding the area of residence or the local supply of such services.

1 The Psychological General Well-Being Index (PGWBI) is a tool to measure self-representations of intra-personal affective or emotional states reflecting a sense of subjective well-being or distress, and thus captures what we could call a subjective perception of well-being. The original PGWBI consists of twenty-two self-administered items, rated on a six-point mood, positive well-being and self-control (see Dupuy, 1990). In this chapter, we have adopted the short form of PGWBI, consisting of six items that generally explain more than 92 per cent of the global variance of the questionnaire. This short version has been validated in a long-term project carried out from 2000 to 2006 in Italy (see Grossi et al., 2006).

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