Social Science & Medicine 100 (2014) 141e147

Contents lists available at ScienceDirect

Social Science & Medicine journal homepage: www.elsevier.com/locate/socscimed

Cognitive social capital and mental illness during economic crisis: A nationwide population-based study in Greece Marina Economou a, b, *, Michael Madianos c, Lily Evangelia Peppou a, Kyriakos Souliotis d, e, Athanasios Patelakis a, Costas Stefanis a a

University Mental Health Research Institute (UMHRI), Athens, Greece First Department of Psychiatry, Medical School, University of Athens, Eginition Hospital, Athens, Greece School of Health Sciences, Department of Mental Health and Behavioral Sciences, University of Athens, Athens, Greece d Faculty of Social Sciences, University of Peloponnese, Corinth, Greece e Center for Health Services Research, Medical School, University of Athens, Athens, Greece b c

a r t i c l e i n f o

a b s t r a c t

Article history: Available online 15 November 2013

The ongoing financial crisis in Greece has yielded adverse effects on the mental health of the population. In this context, the particular study investigates the link between two indices of cognitive social capital; namely interpersonal and institutional trust, and the presence of major depression and generalized anxiety disorder. A random and representative sample of 2256 respondents took part in a cross-sectional nationwide telephone survey the time period FebruaryeApril 2011 (Response Rate ¼ 80.5%), after being recruited from the national phone number databank. Major depression and generalized anxiety disorder were assessed with the Structured Clinical Interview, while for interpersonal and institutional trust the pertinent questions of the European Social Survey were utilized. Socio-demographic variables were also encompassed in the research instrument, while participants’ degree of financial strain was assessed through the Index of Personal Economic Distress. Both interpersonal and institutional trust were found to constitute protective factors against the presence of major depression, but not against generalized anxiety disorder for people experiencing low economic hardship. Nonetheless, in people experiencing high financial strain, interpersonal and institutional trust were not found to bear any association with the presence of the two disorders. Consistent with these, the present study shows that the effect of social capital on mental health is not uniform, as evident by the different pattern of results for the two disorders. Furthermore, cognitive social capital no longer exerts its protective influence on mental health if individuals experience high economic distress. As a corollary of this, interventions aiming at mitigating the mental health effects of economic downturns cannot rely solely on the enhancement of social capital, but also on alleviating economic burden. Ó 2013 Elsevier Ltd. All rights reserved.

Keywords: Economic crisis Financial hardship Major depression Social capital Generalized anxiety disorder Trust

Introduction Social determinants have long been acknowledged as playing a prominent role in health (e.g. House & Kahn, 1985); however, social capital has recently emerged as an increasingly important concept in international research and public health discourse (Kawachi, 2010). While many definitions have been put forward to construe it (e.g. Coleman, 1988; Putnam, 1993), social capital is generally conceptualised as a way of describing social relationships within

* Corresponding author. University Mental Health Research Institute, Soranou tou Efesiou 2, Athens 11527, Greece. E-mail addresses: [email protected] (M. Economou), [email protected] (L.E. Peppou). 0277-9536/$ e see front matter Ó 2013 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.socscimed.2013.11.006

societies or groups of people (De Silva, McKenzie, Harpham, & Huttly, 2005). Given the complexities of the social matrix, the theory of social capital has encompassed various divisions of the concept: ecological vs. individual social capital, structural vs. cognitive social capital, bridging vs. bonding social capital, among others (Almedom, 2005). Its multifaceted nature along with the heterogeneity in definition and measurement has rendered synthesis of evidence challenging. In spite of diversities in the study of social capital, converging evidence has corroborated a link between its indices and health outcomes. For example, it has been shown that components of social capital; such as trust, reciprocity and membership in voluntary organizations, can account for a substantial proportion of life expectancy, infant mortality rate, heart disease, violent crime and self-rated health (Barefoot et al., 1998; Kawachi, Kennedy, & Glass,

142

M. Economou et al. / Social Science & Medicine 100 (2014) 141e147

1999; Kawachi, Kennedy, Lochner, & Pothrow-Stith, 1997; Nummela, Sulander, Rahkonen, Karisto, & Uutela, 2008). On the contrary, only a handful of studies have explored associations between social capital indices and mental health outcomes (Almedom, 2005; De Silva et al., 2005). A systematic review on the association between measures of social capital and mental illness has endeavoured to shed light on their interplay (De Silva et al., 2005). In particular, the results of the review highlight the need to disaggregate/disentangle measurements of ecological social capital from those of individual social capital. While elements of the latter; namely, trust and reciprocity, were found to bear an inverse association with common mental disorders; this does not hold true for ecological social capital and mental illness. The inconsistency in findings emanating from those studies can be explained by the diverging methodologies, the diversity in populations investigated, the variety in mental health outcomes and the different uses of ecological methodology. As a result of these, the authors have been forestalled from drawing firm conclusions. Concomitantly, they call for attention on the dearth of research on studying social capital in rural populations and in developing countries. Nonetheless, the particular systematic review concentrated on negative facets of mental health (i.e. the presence of mental disorders), rather than on overall levels of positive mental health. Congruent with this, a more recent systematic review exploring the links between social capital and mental well-being in older population has shown a positive association between the two (Nyqvist, Forsman, Guintoli, & Cattan, 2013). Similarly, other studies have drawn similar conclusions, justifying further the contribution of social capital in promoting mental health and preventing mental disorders (Forsman, Nyqvist, & Wahlbeck, 2011; Han & Lee, 2013; Muckenhuber, Stronegger, & Freidl, 2013). The need for mental health promotion and disease prevention becomes a top priority during periods of economic downturn (WHO, 2011). In line with this, reports addressing ways of mitigating the mental health effects of the financial crisis, have stressed the importance of strengthening social capital (Christodoulou & Christodoulou, 2013; Wahlbeck & McDaid, 2012). Furthermore, an epidemiological study conducted in 2009 in Sweden revealed an additive impact of low social and economic capital on poor health outcomes, including psychological distress, suggesting that any policy strategies employed should target economic and social capital simultaneously (Ahnquist, Wamala, & Lindstrom, 2012). In spite of the heightened importance of social capital during economic downturn, to date no study has explored its links with mental disorders during a period of economic downturn (Patel, 2010). This strand of research can inform policy making as well as the design and implementation of interventions that can alleviate the mental health impact of the recession. Furthermore, it is congruent with the view that measures of social capital should be embedded in political and economic historical contexts; otherwise they produce partial and distorted accounts of reality (Almedom, 2005). The global economic downturn has been among the deepest to strike the international community since the Great Depression. With its outset being pinpointed in the American continent, the biggest tremors were felt in the Mediterranean countries. Greece, having been gravely struck by the recession, is faced with an ongoing socio-economic and political turmoil, significant cuts in government spending and alarmingly fast-paced increases in unemployment rates (Eurostat, 2011; HSA, 2011). Since 2009, the country is grappling with austerity measures and budget reforms; including the health sector, in an attempt to decrease its fiscal deficits and public debt. While heightened attention is given to the effectiveness of budget cuts and austerity measures in facilitating recovery of the economy; the health effects of the crisis, including

mental health, have recently come to the fore, engendering a lively debate among clinicians, researchers and policy makers (e.g. Kentikelenis et al., 2012; Kondilis, Gavana, Giannakopoulos, & Benos, 2012; Liaropoulos, 2012). As a corollary to the economic downturn, a striking spread of infectious diseases has been observed (Andriopoulos, Economopoulou, Spanakos, & Assimakopoulos, 2012; Bonovas & Nikolopoulos, 2012; Fotiou et al., 2012); while the pernicious health effects of the crisis have also been extended on mental health. In particular, elevated rates of major depression and suicidality have been documented (Economou, Madianos, Peppou, Patelakis, & Stefanis, 2013; Economou et al. 2013; Madianos, Economou, Alexiou, & Stefanis, 2011), while a depression helpline has recorded a steep increase in calls with direct or indirect reference to the economic crisis during the first half of 2010 and onwards (Economou et al., 2012). In 2008, a cross-sectional survey was implemented, so as to compare its findings with those of the first nationwide prevalence study 30 years ago (Madianos, Gefou-Madianou, & Stefanis, 1993; Madianos, Gefou-Madianou, & Stefanis, 1994; Madianos & Stefanis, 1992). In 2009 and in 2011, two replication studies were conducted in order to monitor the impact of the economic crisis on the prevalence of major depression and suicidality in the general population, with both of them corroborating an increase in the pertinent rates, as the crisis progressed (Economou, Madianos, Peppou, Patelakis, et al., 2013; Madianos et al., 2011). In this context, the survey conducted in 2011 incorporated an assessment of two indices of social capital: interpersonal trust (horizontal social capital) and institutional trust (vertical social capital) in an attempt to shed light on the processes taking place in the Greek society at the time. Trust was selected on the grounds that both its horizontal and vertical facets are reciprocally associated with and pertain to the engagement, networks and participation in civil society as well as in the relations of reciprocity in civil society (Putnam, 1993). Furthermore, there is scarcity of research exploring the links between mental illness and trust, especially institutional (Almedom & Glandon, 2008; Lindstrom & Mohensi, 2009). Congruent with the aforementioned, the present paper has set the following objectives: 1) To determine the level of interpersonal and institutional trust in 2011, when the Greek economy was in the throes of collapse. 2) To estimate the association of major depression with interpersonal and institutional trust 3) To estimate the association of generalized anxiety disorder (GAD) with interpersonal and institutional trust. The links between major depression/GAD and interpersonal/ institutional trust will be explored after adjusting for known confounders: gender, age and education (Harpham, Grant, & Thomas, 2002). Concomitantly, a stratified analysis will be conducted for people experiencing high and low economic distress, given the potential moderating role played by economic hardship: “individuals and groups with material assets would be expected to both generate and benefit from the structural and cognitive components for social capital differently from those without” (p. 945, Almedom, 2005). Previous research has shown that high levels of social capital are not always beneficial to mental health and can in fact increase psychological distress in people with low material resources (Kawachi & Berkman, 2001; Mitchell & LaGory, 2002). Consistent with this, the association of social capital indices with mental disorders was explored separately for people in high financial strain and those in low. We expected that the exposure (social capital indices) would have different effects on the outcome (depression and generalized anxiety disorder) at different values of the modifier/moderator variable (high vs. low financial strain).

M. Economou et al. / Social Science & Medicine 100 (2014) 141e147

Methods Sample A random sample of telephone numbers belonging to individuals were drawn from the national phone-number databank, providing coverage for the vast majority of households in the country. The national phone-number databank encompasses numbers of home phones solely, and therefore e mobile phone numbers are not included. Within each household, the person who had their birthday last was selected for the interview; provided that he or she was within the 18e69 age range. At least 5 call backs were allowed. To be included into the study, participants had to be fluent Greek speakers. In total, out of the 2820 calls made, 2256 interviews were successfully completed (Response Rate ¼ 80.5%). In particular, 203 people hung up immediately (7.2%) and 347 (12.3%) refused to be interviewed or did not complete the interview. No statistically significant differences emerged between participants who were interviewed and those who were not in terms of gender, age and place of residence. Concerning the sample composition, it was weighted in terms of gender, age and place of residence to be in line with the 2001 population census (Table 1). Data were collected during FebruaryeApril 2011. Interview schedule For detecting the presence of major depression, the germane module of the Structured Clinical Interview was employed (First, Spitzer, Gibbon, & Williams, 1996). Respondents were asked whether they persistently experienced one or both of the core symptoms of major depression (depressed mood e persistent loss of interest or motivation) for at least two weeks during the previous month. If Table 1 Socio-demographic characteristics of 2011, as compared to those of the population census of 2001. Variables

Gender Males Females Age 65 Marital status Single Married Widowed Divorced Education (years) 13 Place of residence Athens greater area Thessalonica & Central Macedonia Rest of country Occupation Employed Unemployed IPED Low economic distress High economic distress a

Study sample (survey 2011)

Population census (2001)

N

%

%

1090 1166

48.3 51.7

46.8 54.2

223 426 367 425 368 447

9.9 18.9 16.3 18.8 16.3 19.8

9.2 19.8 16.2 19.4 16.0 18.4

455 1585 138 78

20.2 70.3 6.1 3.5

21.0 70.0 7.1 3.0

1351 654 251

59.9 29.0 11.1

61.0 28.0 11.0

847 388 1021

37.5 17.2 45.3

39.3 15.0 45.7

1214 206

85.5 14.5

94.0 6.0

1884 372

83.5 16.5

.a .a

This type of information is not collected during population censuses.

143

participants gave an affirmative response, they were further asked about experiencing 7 additional symptoms most of the time during the same time period. Participants recounting at least 5 symptoms overall, were enquired about the impact of their symptoms in their level of functioning (“were those symptoms made it hard for you to do your work, take care of things at home or get along with other people?”). Furthermore, they were asked about certain events preceding the onset of symptoms: “Just before this began. were you (1) physically ill, (2) using any medications, (3) drinking/using any street drugs”, and (4) “Did this begin after someone close to you died?”. To fulfil DSM-IV criteria for major depression, symptoms could not be accounted for by a general medical condition, the direct physiological effect of a substance (medication or street drugs) or bereavement. Similarly for detecting the presence of GAD, the pertinent section of the Structured Clinical Interview was employed (First et al., 1996). Participants were asked whether they have been (1) particularly nervous or anxious during the past 6 months or (2) worried about bad things that might happen in a variety of events or situations. If respondents gave an affirmative answer, they were asked whether during the last 6 months they have been worried more days than not. In addition, they were enquired about their difficulty in stopping themselves from worrying. If participants met the abovementioned criteria, they were further asked about experiencing at least 3 of the following symptoms for most days during the same time period: (1) feeling on edge, restless; (2) easily becoming fatigued; (3) concentration difficulties; (4) irritability; (5)muscle tension; and (6) sleep disturbance. The focus of anxiety and worry could not be accounted for by features of another Axis I disorder (e.g. about having a panic attack, as in Panic Disorder); participants’ symptoms should have impinged on areas of functioning and the disturbance could not have been caused by the direct physiological effect of a substance (medication or street drugs nor by a general medical condition). The SCID-I has been standardised in the Greek population and has been extensively used in clinical and epidemiological studies (e.g. Madianos, Economou, & Stefanis, 1998; Madianos, Papaghelis, & Philippakis, 1997). The psychometric properties of the assigned diagnosis in the present study were deemed appropriate (Economou, Madianos, Peppou, Patelakis, et al., 2013). Participants’ degree of financial hardship was assessed through the Index of Personal Economic Distress (Madianos et al., 2011), a self-reported scale encompassing 8 questions tapping participants’ difficulty in meeting daily financial demands of a household. Responses are made on a three-point scale reflecting frequency dimension (1 ¼ never, 2 ¼ sometimes, 3 ¼ often). Higher composite scores indicate greater financial distress, with value “15” constituting the cut-off point of the scale, according to the validation of the scale (Madianos et al., 2011). Interpersonal and institutional trust were assessed by the germane questions of the European Social Survey (ESS). The Interpersonal trust section consists of 3 questions rated on a scale from 0 to 10; whereas the institutional trust comprises of 7 questions pertaining to different national and international institutions (e.g. the Police Force, the European Parliament, etc.). Responses are recorded on a scale from 0 to 10. High internal consistency of both sections (Cronbach a ¼ 0.77 for Interpersonal trust and Cronbach a ¼ 0.83 for Institutional trust) justified the use of composite scores in statistical analysis. Procedure After oral informed consent was obtained from the participant the interview was initiated. The method of computer-assisted

144

M. Economou et al. / Social Science & Medicine 100 (2014) 141e147

telephone interviewing was employed (Ketola & Klockars, 1999), since it enables automatic control of questionnaire branching, online verification checks and automatic scheduling of future call backs. All interviews were conducted by well-trained interviewers, graduates in social sciences. The study received approval from the University Mental Health Research Institute Ethics Committee and was executed in line with the ethical standards delineated in the 1964 Declaration of Helsinki.

Table 2 Descriptive statistics for Institutional Trust items.

Parliament Legal system Police Politicians Political parties European Parliament United Nations

Mean

Std. dev.

1.50 2.68 4.02 0.93 0.83 2.79 2.57

2.22 2.54 2.80 1.79 1.69 2.78 2.72

Statistical methods For the descriptive statistics of the composite scores of interpersonal and institutional trust, mean values and standard deviations were calculated. For the second and third research questions, univariate analyses of potential confounders: gender, age, educational status, family status and unemployment were conducted to explore their association with major depression and generalized anxiety disorder. Concomitantly, their link to interpersonal and institutional trust were also investigated by utilizing non-parametric statistics. Variables that were found to bear statistically significant associations with both the outcome of interest (major depression or/and generalized anxiety disorder) and the predictor variable (interpersonal or/and institutional trust) were entered into the logistic regression models as confounders. Gender, age and education were entered as confounder variables in the logistic regression models irrespective of the output of the univariate analyses, following on Harpham et al., suggestions (Harpham et al., 2002). For computing the logistic regression models, Collinearity diagnostics were performed and models displaying very low tolerance values (less than 0.1) were rejected. A separate analysis was conducted for the sample as a whole, for participants experiencing low economic distress (IPED score below the cut-off point 15) and for those experiencing high economic distress (IPED score above the cut-off point). Particularly, for exploring an association between interpersonal trust and major depression, the following logistic regression models were computed: (1) one model including only interpersonal trust alone, (2) one model including interpersonal trust, gender, age and education. A similar approach was employed for interpersonal trust and generalized anxiety disorder. For investigating the association between institutional trust and major depression or generalized anxiety disorder, two regression models were computed: (1) one model including institutional trust alone and (2) one model including institutional trust, gender, age and education. Results

Major depression/generalized anxiety disorder and interpersonal trust Concerning the association between major depression and interpersonal trust, a separate analysis was conducted for the whole sample, participants experiencing high economic distress (cut-off point15). For the sample as a whole, interpersonal trust has a protective effect against major depression, even after adjusting for gender, age and education Table 3). For participants in low economic distress, interpersonal trust alone was found to be a protective factor against major depression (p < 0.05). Particularly, every unit increase in the Interpersonal Trust scale reduces the odds of suffering from major depression by 5% (OR ¼ 0.95, 95% CI ¼ 0.90e0.99). When the confounders were entered in the logistic regression model: gender, age and educational status, the value of OR remained unchanged, lending support to the claim that Interpersonal Trust exerts an independent protective effect against major depression (results are presented in Table 4). On the other hand for participants experiencing high economic distress, the results emerging from the logistic regression are different. Interpersonal Trust does not bear an association with major depression neither alone nor when the confounders are entered into the model (Table 4). In sharp contrast to the findings pertaining to major depression, interpersonal trust was not found to bear a statistically significant association with the presence of GAD in the sample as a whole (Table 3), in people experiencing low financial strain nor in people with high economic distress (Table 4). Major depression/generalized anxiety disorder and institutional trust Similar findings are observed for the association between major depression and institutional trust.

Levels of interpersonal and institutional trust In terms of Interpersonal trust, the mean value in the composite score was found to be 10.8 (sd ¼ 6.3), with score values ranging from 0 to 30. On the contrary, the mean composite score for Institutional trust was found to be particularly low: mean ¼ 15.3, sd ¼ 8.1, scale range ¼ 0 e70. A closer look on the levels of trust for different institutional bodies reveals that the highest trust is expressed towards the Police Force and the lowest towards the political parties (see Table 2). The results of the univariate analyses of potential confounders: gender, age, education, family status and unemployment can be found in Appendix 1 (associations with outcome variables: major depression and generalized anxiety disorder) and in Appendix 2 (associations with predictor variables: interpersonal and institutional trust).

Results for the sample as a whole are similar to those in participants in low economic distress In particular, every unit increase in institutional trust scale reduces the odds of suffering by major depression by 6%, even when confounders are entered into the model (Table 5). On the contrary, in people experiencing high economic distress, institutional trust emerges as a risk factor for major depression (p < 0.05); nonetheless, the effect is confounded by the influence of gender, age and educational status (Table 5). In other words, institutional trust is not associated independently with major depression for people experiencing high financial strain. Similarly, institutional trust could not predict in a statistically significant manner the presence of GAD in the sample as a whole (Table 3), in respondents with low financial strain and in people with high economic distress (Table 5).

M. Economou et al. / Social Science & Medicine 100 (2014) 141e147

145

Table 3 Logistic regression models exploring an association between social capital and mental disorders.

Full sample Interpersonal trust Full sample Institutional trust

Major depression

Generalized anxiety disorder

Or (95% CI)

Or (95% CI)

Model 1

Model 2

Model 1

Model 2

0.95 (0.92e0.98)

0.95 (0.92e0.97)

1.01 (0.92e1.07)

1.01 (0.91e1.09)

0.95 (0.93e0.97)

0.96 (0.94e0.97)

0.99 (0.92e1.06)

0.99 (0.93e1.06)

Model 1: Simple Logistic Regression. Model 2: Multiple Logistic Regression, adjusted for gender, age, and education.

Discussion The aim of the present study has been to explore the levels of institutional and interpersonal trust in the general population in Greece amid economic crisis, and link these two indices of social capital with the presence/absence of major depression and generalized anxiety disorder, while taking into consideration the moderating influence of economic hardship. An indirect comparison between the results of the present study and those emanating from the European Social Survey (ESS Round 1, 2002; ESS Round 2, 2004; ESS Round 3, 2006; ESS Round 4, 2008) reveal that in spite of the different sampling procedures employed in the two study designs and minor differences in methodology, the degree of interpersonal trust has remained stable since 2002 (mean values range from 10.3 in 2002 to 10.9 in 2008). On the other hand, a downward spiral is observed with regard to institutional trust mean values: 32.6 in 2004, 26.5 in 2008 and 15.3 in 2011. It is the authors’ point of view and it is only a speculation that the aforementioned differences cannot be explained by differences in methodology; otherwise, a similar pattern would have been observed for interpersonal trust findings; but they probably reflect changes and processes occurring in the political and socioeconomic climate of the time. In particular, 2004 was a prosperous year for the Greek economy with the Olympic games occurring in the country. Since then, a gradual decline in the Greek economy was observed along with a growing scepticism towards political parties and politicians, culminating during the onset of the financial crisis in the country in 2009 and the prevention of economic collapse in 2010. The particular findings are in line with model of vertical social capital (Woolcock, 1998) and therefore stress the importance of expanding attention to its facets and indices in order to grasp the health outcomes of groups and individuals (McKenzie, Whitley, & Weich, 2002). Concerning the association between social capital and mental illness, both interpersonal and institutional trust were found to protect against the presence of major depression in the sample as a whole and in respondents experiencing low levels of financial strain, even after adjusting for a potential confounder effect of gender, age and educational status. The protective effect of trust against depression is reminiscent of Putnam’s remark on the “depression

epidemic” in USA, where the Amish Community in Pennsylvania may have been spared due to the closely-knit community characterized by strong norms of trust (Putnam, 2000). Low levels of trust to others (interpersonal trust) and to the Swedish parliament (institutional trust) have also been reported to be associated with poor self-reported psychological health in a cross-sectional public health survey in Sweden (Lindstrom & Mohensi, 2009). In the present study, while depression was found to be inversely associated with cognitive social capital for people in low economic hardship, this did not hold true for generalized anxiety disorder. Congruent with this, the present study is in partial agreement with a systematic review corroborating an inverse link between cognitive social capital and common mental disorders (De Silva et al., 2005), and in partial agreement with Cultrona and colleagues who have reported a non-significant association between depression/anxiety and perceived social cohesion (respondents’ views on trust and neighbourhood relations) in 700 African-American mothers of 10e12 year-olds (Cutrona, Russell, Hessling, Brown, & Murry, 2000). It is likely that high levels of interpersonal and institutional trust can protect one against depression via him/her holding a positive outlook on his/her environment and the future as well as via establishing a social support system around him/her. On the other hand, high levels of trust cannot protect against the pervasive and uncontrollable anxiety and worry characterizing generalized anxiety disorder, which are often triggered even by minor events in daily life. It is highly likely that interpersonal/ institutional trust may alleviate the anxiety triggered by certain stimuli but cannot cover the full range of events eliciting worry in people who suffer from GAD. The different trajectories displayed by depression and generalized anxiety disorder are consistent with a recent study exploring the link between social capital and postdisaster mental health (Wind, Fordham, & Komproe, 2011). It merits discussing that both major depression and GAD were not found to bear an association with social capital for people experiencing high economic distress indicating a potential moderating influence of economic hardship. The observation that a significant association between major depression and trust was found for the sample as a whole as well as for people experiencing low economic distress but not for those experiencing high is probably explained by the over-representation of people in low

Table 4 Logistic regression models for interpersonal trust and mental disorders. Major depression

Generalized anxiety disorder

Or (95% CI)

Low economic distress Interpersonal trust High economic distress Interpersonal trust

Or (95% CI)

Model 1

Model 2

Model 1

Model 2

0.95 (0.90e0.99)

0.95 (0.91e0.99)

1.02 (0.94e1.09)

1.01 (0.93e1.09)

1.01 (0.94e1.06)

0.98 (0.93e1.05)

0.98 (0.87e1.10)

1.00 (0.88e1.12)

Model 1: Simple Logistic Regression. Model 2: Multiple Logistic Regression adjusted for gender, age and education.

146

M. Economou et al. / Social Science & Medicine 100 (2014) 141e147

Table 5 Logistic regression models for institutional trust and mental disorders.

Low economic distress Institutional trust High economic distress Institutional trust

Major depression

Generalized anxiety disorder

Or (95% CI)

Or (95% CI)

Model 1

Model 2

Model 1

Model 2

0.94 (0.90e0.96)

0.94 (0.91e0.97)

0.99 (0.95e1.04)

0.99 (0.95e1.04)

1.03 (1.01e1.05)

1.03 (0.99e1.05)

0.95 (0.86e1.05)

0.95 (0.84e1.06)

Model 1: Simple Logistic Regression. Model 2: Multiple Logistic Regression, adjusted for gender, age, and education.

economic distress in the sample (83.5%), indicating that the moderating effect of economic hardship might have been overlooked if the sample was not stratified. This is in line with the theoretical standpoint of Almedom (2005) who has maintained that people with material assets are expected to generate and benefit from the various elements of social capital differently from those without. In this line of reasoning, Kawachi and Berkman (2001) have contended that the protective influence of social support on mental health may not be uniform across society. From their standpoint, social connections may actually enhance distress among women with low resources, if such connections necessitate reciprocal obligations, such as providing support to others. Findings from a high-poverty racially segregated urban neighbourhood in a mid-sized southern city in USA lends credence to this view, as bonding social capital was linked to elevated rates of mental distress (Mitchell & LaGory, 2002). In particular, the researchers of the aforementioned study argued that community connections were less likely to act as an asset network and more likely to engender a number of obligations. Thus, people living there had to cope with both their own economic and environmental stressors as well as with the obligations created by the strong ties in the community. In line with these, it appears that social capital can also act as a risk factor for mental disorders in communities with low material assets. In the present study, people experiencing high financial strain were found to be no longer protected by the cognitive components of social capital. It seems that their close relationships to other people may result in additional emotional burden through social contagion pathways. Moreover, the multifaceted difficulties pertaining to their financial state render them particularly vulnerable to major depression through numerous routes, with only some of them being influenced by cognitive social capital. In line with these, the findings of the present study echo the conclusion drawn by Phongsavan and colleagues that promoting social capital alone without addressing socio-economic indicators may be ineffective as a strategy for enhancing mental health and preventing the incidence of mental disorders (Phongsavan, Chey, Bauman, Brooks, & Silove, 2006). Similar suggestions are made by Ahnquist et al. (2012), who have argued that social and economic capital should be targeted simultaneously, as low levels in both constructs have a combining adverse influence on health. Strengths and limitations To the authors’ knowledge this is the first study which has endeavoured to explore the link between cognitive social capital and mental disorders during a period of economic downturn. It has integrated measures of both horizontal and vertical social capital, while mental disorders were assessed through a clinically relevant instrument with good psychometric properties. In addition, a nationwide population sample was recruited and the response rate was particularly high.

However, there are study limitations which warrant consideration. While the study sample was representative of the population, particular segments of the population were under-represented; mainly homeless individuals and immigrants. The former category was excluded due to the telephone mode of data collection, while immigrants could only take part in the study if they were fluent in the Greek language. Furthermore, a culturally-sensitive clinical instrument for diagnosing major depression and generalized anxiety disorder in this population group would have been more appropriate to avoid misclassification bias. Consistent with this, population sub-groups who are particularly susceptible to the influence of the crisis and at the same time are at high risk of mental disorders have not been taken into consideration, raising therefore the possibility of a sampling bias in the study design. A subsequent prevalence survey should circumvent this shortcoming, possibly by recruiting participants from local rations or by conducting a study focussing exclusively on these population subgroups. Another study limitation, which is inherent to cross-sectional surveys, concerns the direction of causality. In particular, one cannot draw any causal inferences on the relationship between social capital indices and mental disorders, as it is unclear whether low social capital results in the presence of mental disorders or vice versa, the presence of these disorders results in low levels of social capital. Furthermore, the study gleaned social capital -related data only from individual responses, without incorporating collective indices, as suggested by Kawachi et al., (Kawachi, Kim, Couts, & Subramanian, 2004). The rationale for this omission is related to the research aim of the particular epidemiological survey, which focused on gauging the impact of the financial crisis on the mental health of the Greek population (Economou, Madianos, Peppou, Patelakis, et al., 2013; Economou et al. 2013; Madianos et al., 2011). The investigation of the link between social capital and mental illness was a secondary objective of the survey and this is the main reason why other indices of cognitive social capital, such as social participation (social networks, social support, etc.) were not taken into account. Nonetheless, a future study should address in depth the associations of social capital with mental disorders, by entailing both individual and collective indices and by analyzing them simultaneously within a multilevel analytical framework. In conclusion, the interplay between social capital and mental disorders amid economic crisis is not uniform. It appears that cognitive social capital can protect against major depression but not against generalized anxiety disorder in people experiencing low financial strain. For people experiencing high economic hardship, social capital does no longer exert its protective influence. In line with this, interventions aiming at mitigating the mental health effects of financial hardship should target simultaneously the promotion of social capital and the alleviation of economic burden. In particular, health policy planning should focus on the improvement of trust towards health institutions, primarily those related to the provision of publicly funded health care. Such trust, and service demand was in the past concentrated in a wide

M. Economou et al. / Social Science & Medicine 100 (2014) 141e147

network of privately funded providers (Tountas, Karnaki, Pavi, & Souliotis, 2005), an option no longer available to the majority of the population given the radical reduction in household incomes. Concomitantly, in order to strengthen trust in the social capital and related institutions, one should address the issue at its core: i.e. the circumstances that lead to financial distress and difficulties. Tackling such circumstances would involve public policies for the redistribution of income and the support of vulnerable population groups, many of which are now faced with social exclusion. Appendix A. Supplementary data Supplementary data related to this article can be found at http:// dx.doi.org/10.1016/j.socscimed.2013.11.006. References Ahnquist, J., Wamala, S. P., & Lindstrom, M. (2012). Social dfeterminants of health e a question of social or economic capital? Interaction effects of socioeconomic factors on health outcomes. Social Science & Medicine, 74, 930e939. Almedom, A. M. (2005). Social capital and mental health: an interdisciplinary review of primary evidence. Social Science & Medicine, 61, 943e964. Almedom, A. M., & Glandon, D. (2008). Social capital and mental health: an updated interdisciplinary review of primary evidence. In I. Kawachi, S. V. Subramanian, & D. Kim (Eds.), Social capital and health (pp. 191e214). New York: Springer. Andriopoulos, P., Economopoulou, A., Spanakos, G., & Assimakopoulos, G. (2012). A local outbreak of autochthonous Plasmodium vivax malaria in Lakonia, Greece-a re-emerging infection in the southern borders of Europe? International Journal of Infectious Diseases, 17, e125ee128. Barefoot, J. C., Maynard, K. E., Beckham, J. C., Brummett, B. H., Hooker, K., & Siegler, I. C. (1998). Trust, health and longevity. Journal of Behavioral Medicine, 21, 517e526. Bonovas, S., & Nikolopoulos, G. (2012). High-burden epidemics in Greece in the era of economic crisis. Early signs of a public health tragedy. Journal of Preventive Medicine and Hygiene, 53, 169e171. Christodoulou, N. G., & Christodoulou, G. N. (2013). Management of the psychosocial effects of economic crises. World Psychiatry, 12, 178. Coleman, J. S. (1988). Social capital in the creation of human capital. American Journal of Sociology, 94, 95e120. Cutrona, C. E., Russell, D. W., Hessling, R. M., Brown, P. A., & Murry, V. (2000). Direct and moderating effects of community context on the psychological well-being of African American women. Journal of Personality and Social Psychology, 79, 1088e1101. De Silva, M. J., McKenzie, K., Harpham, T., & Huttly, S. R. A. (2005). Social capital and mental illness: a systematic review. Journal of Epidemiology & Community Health, 59, 619e627. Economou, M., Madianos, M., Peppou, L. E., Patelakis, A., & Stefanis, C. (2013). Major depression in the era of economic crisis: a replication of a cross-sectional study across Greece. Journal of Affective Disorders, 145, 308e314. Economou, M., Madianos, M., Peppou, L. E., Theleritis, C., Patelakis, A., & Stefanis, C. (2013). Suicidal ideation and reported suicide attempts in Greece during the economic crisis. World Psychiatry, 12, 53e59. Economou, M., Peppou, L. E., Louki, E., Komporozos, A., Mellou, A., & Stefanis, C. (2012). Depression telephone helpline: help-seeking during the financial crisis. Psychiatriki, 23, 17e28. ESS Round 1: European Social Survey Round 1 Data. (2002). Data file edition 6.3. Norway: Norwegian Social Science Data Services. Data Asrchive and distributor of ESS data. ESS Round 2: European Social Survey Round 2 Data. (2004). Data file edition 3.3. Norway: Norwegian Social Science Data Services. Data Archive and distributor of ESS data. ESS Round 3: European Social Survey Round 3 Data. (2006). Data file edition 3.4. Norway: Norwegian Social Science Data Services. Data Archive and distributor of ESS data. ESS Round 4: European Social Survey Round 4 Data. (2008). Data file edition 4.1. Norway: Norwegian Social Science Data Services. Data Archive and distributor of ESS data. Eurostat. (2011). Euro area and EU27 government deficit at 6.0% and 6.4% of GDP respectively. Luxembourg: Eurostat. First, M. B., Spitzer, R., Gibbon, M., & Williams, J. B. W. (1996). Structured clinical interview for DSM IV axis I disorders. Patient edition. New York: Biometrics Research, New York State Psychiatric Institute. Forsman, A. K., Nyqvist, F., & Wahlbeck, K. (2011). Cognitive components of social capital and mental health status among older adults: a population-based crosssectional study. Scandinavian Journal of Public Health, 39, 757e765. Fotiou, A., Micha, K., Paraskevis, D., Terzidou, M., Malliori, M. M., & Hatzakis, A. (2012). HIV outbreak among injecting drug users in Greece: An updated report for

147

the EMCDDA on the recent outbreak of HIV infections among drug injectors in Greece. Athens: European Monitoring Centre for Drugs and Drug Addiction. Han, S., & Lee, H. S. (2013). Individual, household and administrative area levels of social capital and their associations with mental health: a multivel-analysis of cross-sectional evidence. International Journal of Social Psychiatry, 59, 716e723. Harpham, T., Grant, E., & Thomas, E. (2002). Measuring social capital within health surveys: key issues. Health Policy & Planning, 17, 106e111. Hellenic Statistical Authority. (2011). Unemployment rate at 16.6% in May 2011. Piraeus: HSA. House, J. S., & Kahn, R. (1985). Measures and concepts of social support. In S. Cohen, & S. L. Syme (Eds.), Social support and health (pp. 83e108). Orlando, FL: Academic Press. Kawachi, I. (2010). Social capital and health. In C. E. Bird, P. Conrad, A. M. Fremont, & S. Timmermans (Eds.), Handbook of medical sociology (pp. 18e32). Tenness: Vanderbilt University Press. Kawachi, I., & Berkman, L. (2001). Social ties and mental health. Journal of Urban Health, 78, 458e467. Kawachi, I., Kennedy, B. P., & Glass, R. (1999). Social capital and self-rated health: a contextual analysis. American Journal of Public Health, 89, 1187e1193. Kawachi, I., Kennedy, B. P., Lochner, K., & Pothrow-Stith, D. (1997). Social capital, income inequality, and mortality. American Journal of Public Health, 87, 1491e1498. Kawachi, I., Kim, D., Couts, A., & Subramanian, S. V. (2004). Commentary: reconciling the three accounts of social capital. International Journal of Epidemiology, 33, 682e690. Kentikelenis, A., Karanikolos, M., Papanicolas, I., Basu, S., McKee, M., & Stuckler, D. (2012). Re: Greek economic crisis: not a tragedy for health. British Medical Journal, 345, e8608. Ketola, E., & Klockars, M. (1999). Computer-assisted telephone interview (CATI) in primary care. Family Practice, 16, 179e183. Kondilis, E., Gavana, M., Giannakopoulos, S., & Benos, A. (2012). Re: Greek ecomomic tragedy: not a tragedy for health. British Medical Journal, 345, e7988. Liaropoulos, L. (2012). Greek economic crisis: not a tragedy for health. British Medical Journal, 345, e7988. Lindstrom, M., & Mohensi, M. (2009). Social capital, political trust and self-reported psychological health: a population-based study. Social Science & Medicine, 68, 436e443. Madianos, M., Papaghelis, M., & Philippakis, A. (1997). The reliability of SCID I in Greece in clinical and general population. Psychiatriki, 8, 101e108. Madianos, M., Economou, M., Alexiou, T., & Stefanis, C. (2011). Depression and economic hardship across Greece in 2008 and 2009: two cross-sectional surveys nationwide. Social Psychiatry and Psychiatric Epidemiology, 46, 943e952. Madianos, M., Economou, M., & Stefanis, C. (1998). Long-term outcome of psychiatric disorders in the community: a 13 year follow up study in a nonclinical population. Comprehensive Psychiatry, 39, 47e56. Madianos, M. G., Gefou-Madianou, D., & Stefanis, C. (1993). Changes in suicidal behavior among nationwide general population samples across Greece. European Archives of Psychiatry and Clinical Neuroscience, 243, 171e178. Madianos, M. G., Gefou-Madianou, D., & Stefanis, C. (1994). Symptoms of depression, suicidal behavior and use of substances in Greece: a nationwide general population survey. Acta Psychiatrica Scandinavica, 89, 159e166. Madianos, M., & Stefanis, C. (1992). Changes in the prevalence of symptoms of depression and depression across Greece. Social Psychiatry and Psychiatric Epidemiology, 27, 211e219. McKenzie, K., Whitley, R., & Weich, S. (2002). Social capital and mental health. British Journal of Psychiatry, 181, 280e283. Mitchell, C. U., & LaGory, M. (2002). Social capital and mental distress in an impoverished community. City & Community, 1, 199e222. Muckenhuber, J., Stronegger, W., & Freidl, W. (2013). Social capital affects the health of older people more strongly than that of younger people. Ageing & Society, 33, 853e870. Nummela, O., Sulander, T., Rahkonen, O., Karisto, A., & Uutela, A. (2008). Social participation, trust and self-rated health: a study among ageing people in urban, semi-urban and rural settings. Health & Place, 14, 243e253. Nyqvist, F., Forsman, A. K., Guintoli, G., & Cattan, M. (2013). Social capital as a resource for mental well-being in older adults: a systematic review. Aging & Mental Health, 17, 394e410. Patel, V. (2010). Building social capital and improving mental health care to prevent suicide. International Journal of Epidemiology, 39, 1411e1412. Phongsavan, P., Chey, T., Bauman, A., Brooks, R., & Silove, D. (2006). Social capital, socio-economic status and psychological distress among Australian adults. Social Science & Medicine, 63, 2546e2561. Putnam, R. (1993). Making democracy work: Civic traditions in modern Italy. Princeton, NJ: Princeton University Press. Putnam, R. (2000). Bowling alone: The collapse and revival of American community. New York: Simon & Schuster. Tountas, Y., Karnaki, P., Pavi, E., & Souliotis, K. (2005). The “Unexpected” growth of the private health sector in Greece. Health Policy, 74, 167e180. Wahlbeck, K., & McDaid, D. (2012). Actions to alleviate the mental health impact of the economic crisis. World Psychiatry, 11, 139e145. Wind, T. R., Fordham, M., & Komproe, I. H. (2011). Social capital and post-disaster mental health. Global Health Action, 4, 10.3402/gha.v4i0.6351. Woolcock, M. (1998). Social capital and economic development: towards a theoretical synthesis and policy framework. Theory & Society, 2, 151e208. World Health Organization. (2011). Impact of economic crises on mental health. Geneva: WHO.

Cognitive social capital and mental illness during economic crisis: a nationwide population-based study in Greece.

The ongoing financial crisis in Greece has yielded adverse effects on the mental health of the population. In this context, the particular study inves...
270KB Sizes 0 Downloads 0 Views