PDF file of entire paper: Print-quality (285K)

K07020; Online publication date 30 May 2008
Received 9 November 2007; accepted 19 March 2008
Kōtuitui: New Zealand Journal of Social Sciences Online, 2008, Vol. 3: 15–20
1177–083X/08/0301–15  © The Royal Society of New Zealand 2008

Kōtuitui

New Zealand Journal of Social Sciences Online

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Research note

Does social capital predict happiness, health, and life satisfaction in an urban Australian community?

Evonne Miller^*

Laurie Buys

School of Design
Queensland University of Technology
GPO Box 2434
Brisbane, Queensland, Australia 4001

e.miller@qut.edu.au
l.buys@qut.edu.au

^*Author for correspondence

Abstract  This paper investigates the extent to which social capital and participation in community activities predicts happiness, health, and life satisfaction in Australia. Residents of a Gold Coast suburb completed a random door-to-door survey, with a 74% response rate ( n = 249). Ordinal regression analyses revealed that only two elements of social capital—Value of Life and Feelings of Trust and Safety—predicted happiness (β = 0.4, P = 0.00; β = 0.12, P = 0.00), life satisfaction (β = 0.46, P = 0.00; β = 0.09, P = 0.02), and health (β = 0.29, P = 0.00; β = 0.11, P = 0.00). In terms of community activities, not participating in social activities predicted both unhappiness (β = –0.16, P = 0.05) and reduced life satisfaction (β = –0.20, P = 0.01). Such findings suggest that how social capital is defined and measured is important, as only two of the seven elements—life satisfaction and health—predicted happiness. The key implication is that implementing strategies, initiatives, and urban designs that facilitate feelings of trust and safety may foster health, happiness, and life satisfaction.

Keywords  social capital; health; happiness; life satisfaction; urban community

INTRODUCTION

Social capital, succinctly defined as the social connectedness of a community, is frequently described as a critical element of public health promotion in the 21st century (Wakefield & Poland 2005). A growing body of research has linked social capital measured at the national, state, neighbourhood, and individual level with positive health outcomes, recent Australian studies demonstrating that perceived neighbourhood safety predicts physical health while both neighbourhood connections and safety predicted mental health (Ziersch et al. 2005; Philayrath et al. 2006).

  Despite such promising findings, the concept of social capital has been criticised on several levels. First, a key criticism of social capital is the issue of causality, as a clear causal relationship between social capital and health is difficult to identify (Rudd 2000). Second, there is ongoing debate over how the multidimensional and often ambiguous concept of social capital should be conceptualised, defined, and measured (Wakefield & Poland 2005). There is no universal definition of social capital, with theorists variously conceptualising it as an attribute of the community (Putnam 2000), institutional/organisational structures (Coleman 1988), and as a resource (Bourdieu 1986). This lack of conceptual clarity means that the definition and indicators of social capital differ substantially from study to study, with the concept of social capital “stretched, modified, and extrapolated to cover so many levels of individual, group, institutional, and state analysis that the term has lost all heuristic value” (Macinko & Starfield 2001: 394). Without a consensus on how to define or operationalise social capital, researchers often utilise existing datasets and proxy items not originally designed to measure social capital (Baum & Ziersch 2003). For example, data from the General Social Survey in America has been re-analysed to demonstrate that social capital, operationalised as interpersonal trust and membership in voluntary groups, is linked to reduced mortality (Kawachi et al. 1997). Moreover, the lack of a validated and widely utilised scale for measuring social capital means that public health researchers frequently develop their own social capital indicators, further limiting comparability (Ziersch et al. 2005; Philayrath et al. 2006).

  Although the measurement of social capital is still in its infancy, several researchers have developed standardised scales that provide, for the first time, an empirically validated tool for exploring if and how different dimensions of social capital might affect public health. For example, Putnam (2000) has utilised a 14-indicator index combining individual responses and aggregated data, while Carpiano (2007) recently developed a scale measuring six dimensions of neighbourhood and individual-level social capital, including social cohesion, informal social control, and neighbourhood attachment. An increasingly popular measure of social capital is Onyx & Bullen’s (2000) Australian-based eight-element measure of social capital, which has been validated in the United States (O’Brien et al. 2004) and Greece (Kritsotakis et al. 2008). To date, these social capital scales have not been utilised widely by public health researchers. Thus, this research utilises the Australian-based measure to explore the extent to which social capital predicts the health, happiness, and life satisfaction of residents in an urban Australian community.

METHOD

Participants were a random sample of residents from a typical residential urban suburb located in the Gold Coast, in Queensland, Australia, who agreed to complete a door-to-door survey on social capital and sustainability (Miller & Buys 2008). Each randomly selected household within the catchment area received a brochure explaining the project and notification about when interviewers would be visiting to distribute and collect questionnaires in their neighbourhood over a 2-week period. There was a 74% response rate, with 249 residents included in the analysis. This article focuses on a subset of this survey, specifically basic demographic information, seven sub-scales from Onyx & Bullen’s (2000) 36-item social capital scale (Table 1), and 22 dichotomous (yes/no) questions assessing participation in community activities: nine local activities (e.g., shop locally), eight outdoor activities (e.g., use local parks), and five social activities (e.g., family get-togethers). The dependent variables were overall happiness, life satisfaction, and good health, assessed via 5-point Likert scales anchored at “never” and “always”. Utilising SPSS software, composite scores were created for the social capital sub-scales (Table 1.) and community participation measures. As the dependent variables were ordered categories (1 = “never” to 5 = “always”), ordinal regression analyses with complementary log-log link function were conducted to determine which variables predicted happiness, life satisfaction, or health.

RESULTS

The mean age of respondents was 44 years, ranging from 17 to 82 years, with 53% female. The majority were employed (69%) and had children (51%), with over half (60%) reporting a total household income of less than A$50 000 a year. On average, respondents reported participating in six local activities (range = 1–9, SD = 1.8), five outdoor activities (range = 0–9, SD = 2.1), and three social activities (range = 0–5, SD = 1.5), and relatively high mean levels of happiness (M = 4.3, SD = 0.649), life satisfaction (M = 4.24, SD = 0.711), and good health (M = 4.29, SD = 0.721).

  Ordinal regression analyses with complementary log-log link function were modelled to investigate whether demographic variables, social capital, outdoor and social activities predicted happiness, life satisfaction, or health (Table 2.). Happiness [χ² (15, N = 248) = 85.05, P = 0.000] was predicted by two aspects of social capital, Value of Life [β = 0.4, Wald χ² = 28.6, P = 0.000] and Feelings of Trust and Safety [β = 0.12, Wald χ² = 8.3, P = 0.004], reduced participation in social activities [β = –0.16, Wald χ² = 4.03, P = 0.045] and, marginally, greater participation in outdoor activities [β = 0.09, Wald χ² = 3.16, P = 0.075]. Happiness was also predicted by higher income [β = 0.12, Wald χ² = 6.02, P = 0.014] and, marginally, being older [β = 0.01, Wald χ² = 2.79, P = 0.095].

  Life satisfaction [χ² (15, N = 249) = 102.17, P = 0.000] was predicted by two aspects of social capital, Value of Life [β = 0.46, Wald χ² = 38.31, P = 0.000] and Feelings of Trust and Safety [β = 0.09, Wald χ² = 5.4, P = 0.02]. Lower scores on the Family and Friends sub-scale was marginally associated with increased life satisfaction [β = –0.09, Wald χ² = 3.2, P = 0.074]. Reduced participation in social activities [β = –0.20, Wald χ² = 6.18, P = 0.013] and greater participation in outdoor activities [β = 0.12, Wald χ² = 6.43, P = 0.011] predicted life satisfaction. Higher income [β = 0.10, Wald χ² = 3.72, P = 0.054] and not working [β = 0.41, Wald χ² = 2.79, P = 0.095] were marginally significant predictors of life satisfaction.

  Health [χ² (15, N = 249) = 43.64, P = 0.000] was predicted by two aspects of social capital, Value of Life [β = 0.29, Wald χ² = 17.78, P = 0.000] and Feelings of Trust and Safety [β = 0.11, Wald χ² = 8.70, P = 0.003], with women marginally more likely to report better health than men [β = 0.36, Wald χ² = 3.32, P = 0.069].

DISCUSSION

This research, the first to utilise a standardised scale to measure social capital and its effect on health, happiness and life satisfaction, highlights two issues of considerable significance to researchers, policy makers, and urban planners. The first is that two elements of social capital—Value of Life and Feelings of Trust and Safety—were consistent predictors of health, happiness and life satisfaction. Notably, the five other elements of social capital, including Neighbourhood Connections and Participation in Local Community, did not. This discrepancy in the predictive value of different elements of social capital is generally consistent with previous research, with the neighbourhood safety element of social capital frequently the key predictor of health (Ziersch et al. 2005; Philayrath et al. 2006). Such consistent findings suggest that implementing strategies, infrastructure, and urban plans designed to facilitate trust and safety may have positive implications for public health and community wellbeing (Sampson 2001; Ferguson & Mindel 2007).

  From a practical policy and planning perspective, therefore, this research reinforces the importance of prioritising initiatives designed to enhance community safety, which may also simultaneously help build social capital and individual health. Traditionally, health promotion and preventative strategies have focused primarily on individuals. However, with this research suggesting that investing in community safety may enhance individual health, a priority must be to foster communication and collaboration among policymakers from the traditionally disparate areas of health, community infrastructure, safety, and policing. A key intervention strategy implied by this research, therefore, is to prioritise community-focused interventions that foster both safety and social interactions.

  The second issue concerns the complexity of social capital and health interrelationships, alluded to above. Despite utilising a comprehensive and internationally validated measure, the public health predictive value of social capital was relatively low (only two of seven sub-scales), with our measure of community activities actually linking reduced participation in social activities to happiness and life satisfaction. Such inconsistencies highlight the importance of utilising comparable social capital indicators, which ensures findings from different studies can be merged, via meta-analytic techniques, to develop a consensus about the most appropriate public health implications and recommendations. To enhance comparability, therefore, wherever possible researchers should endeavour to use existing measures of social capital.

  The limitations of this exploratory cross-sectional research must be acknowledged, specifically the relatively small sample size, measurement of social capital at the individual level only, developing our own non-validated measure of participation in community activities, and the reliance on single-item self-report indicators of health, happiness, and life satisfaction. In particular, the correlational research design means causal inferences cannot be made regarding the relationship between social capital and health, which may be explained by reverse causality. For example, people may report higher levels of social capital because they are healthier or happier, rather than the other way around. Potentially, happy people may have more feelings of trust and safety as a result of being happy. As only experimental and longitudinal studies can address such questions of causality, more research is needed to better understand the role social capital might play in health and identify the causal pathways. Despite inherent difficulties in defining and measuring social capital, however, researchers agree it has the potential to significantly improve public health “if we can reduce it to doable actions” (Leeder & Dominello 1999: 429). This research indicates that one “doable action” that may positively impact on public health, specifically health, happiness and life satisfaction, is building the trust and safety element of social capital.

ACKNOWLEDGMENTS

The authors acknowledge the Queensland Department of Public Works and the Gold Coast City Council for providing the funding to conduct this research. We thank Nikki David for statistical support.

REFERENCES

Baum F, Ziersch AM 2003. Social capital. Journal of Epidemiology and Community Health 57: 320–323.

Bourdieu P 1986. The forms of capital. In: Richardson JG ed. Handbook of theory and research for the sociology of education. New York, Greenwood Press. Pp. 241–258.

Carpiano RM 2007. Neighborhood social capital and adult health: an empirical test of a Bourdieu-based model. Health & Place 13(3): 639–655.

Coleman J 1988. Social capital in the creation of human capital . American Journal of Sociology 94: S95–S120.

Ferguson KM, Mindel CH 2007. Modeling fear of crime in Dallas neighborhoods: a test of social capital theory. Crime & Delinquency 53(2): 322–349.

Kawachi I, Kennedy BP, Lochner K, Prothrow-Stith D 1997. Social capital, income inequality, and mortality. American Journal of Public Health 87: 1491–1498.

Kritsotakis G, Koutis AD, Alegakis AK, Philalithis AE 2008. Development of the social capital questionnaire in Greece. Research in Nursing & Health 31(3): 217–225.

Leeder S, Dominello A 1999. Social capital and its relevance to health and family policy. Australia & New Zealand Journal of Public Health 23(4): 424–429.

Macinko J, Starfield B 2001. The utility of social capital in research on health determinants. The Milbank Quarterly 79(3): 387–427.

Miller E, Buys L 2008. The impact of social capital on residential water-affecting behaviors in a drought-prone Australian community . Society & Natural Resources 21(3): 244–257.

O’Brien MS, Burdsal CA, Molgaard CA 2004. Further development of an Australian-based measure of social capital in a US sample. Social Science & Medicine 59(6): 1207–1217.

Onyx J, Bullen P 2000. Measuring social capital in five communities. Journal of Applied Behavioral Science 36(1): 23–42.

Philayrath 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(10): 2546–2561.

Putnam RD 2000. Bowling alone: the collapse and revival of American community. New York, Simon & Schuster.

Rudd MA 2000. Live long and prosper: collective action, social capital and social vision. Ecological Economics 34(234): 131–144.

Sampson RJ 2001. Crime and public safety: insights from community-level perspectives on social capital. In: Saegert S, Thompson JP, Warren MR ed. Social capital and poor communities . New York, Russell Sage. Pp. 89–114.

Wakefield SE, Poland B 2005. Family, friend or foe? Critical reflections on the relevance and role of social capital in health promotion and community development. Social Science & Medicine 60(12): 2819–2832.

Ziersch AM, Baum FE, MacDougall C, Putland C 2005. Neighbourhood life and social capital: the implications for health. Social Science & Medicine 60: 71–86.

Table 1  Mean scores for the seven elements of social capital and general score.

Elements of social capital	Sample item	Mean scores
Capacity building blocks
Social Agency (5 questions, 20 highest possible score)	Do you go outside your local community to visit your family?	16.2
Feelings of Trust & Safety (5 questions, 20 highest possible score)	Do you agree that most people can be trusted?	12.8
Tolerance of Diversity (2 questions, 8 highest possible score)	Do you think that multiculturalism makes life in your area better?	6.1
Value of Life (2 questions, 8 highest possible score)	Do you feel valued by society?	5.8
Social arenas
Neighbourhood Connections (5 questions, 20 highest possible score)	Have you visited a neighbour in the past week?	12.8
Family & Friends (3 questions, 12 highest possible score)	Can you get help from friends when you need it?	9.4
Participation in Local Community (7 questions, 28 highest possible score)	Do you help out a local group as a volunteer?	11.5
General SC		74.8

 

Table 2  Predictors of happiness, life satisfaction, and health.

	Happiness			Life satisfaction			Health
	β	Wald		β	Wald		β	Wald
Social capital
Value of Life	0.396***	28.598		0.463***	38.305		0.291***	17.780
Feelings of Trust & Safety	0.115**	8.298		0.090*	5.397		0.111**	8.704
Participation in Local Community	0.011	0.152		0.023	0.699		–0.036	2.023
Neighbourhood Connections	–0.002	0.003		0.049	2.401		–0.005	0.029
Proactivity in a Social Context	0.043	1.254		–0.008	0.048		0.007	0.037
Family & Friends	–0.025	0.229		–0.093^	3.201		–0.077	2.166
Tolerance of Diversity	0.058	0.961		0.093	2.645		0.027	0.247
Activities
Local	–0.040	0.400		–0.061	0.955		–0.013	0.043
Outdoor	0.088^	3.163		0.124*	6.428		0.072	2.300
Social	–0.163*	4.026		–0.199*	6.175		–0.040	0.266
Demographics
Age	0.013^	2.790		0.012	2.337		–0.005	0.469
Income	0.124*	6.023		0.097^	3.715		0.003	0.004
Employed	0.351	1.999		0.414^	2.794		–0.039	0.027
Children	0.008	0.002		0.168	0.667		–0.237	1.345
Gender	0.214	1.064		0.096	0.221		0.361^	3.318

 *** P < 0.001, ** P < 0.01, * P < 0.05, ^ P < 0.10. Significant values are bold.

 

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PDF file of entire paper: Print-quality (285K)

K07020; Online publication date 30 May 2008
Received 9 November 2007; accepted 19 March 2008
Kōtuitui: New Zealand Journal of Social Sciences Online, 2008, Vol. 3: 15–20
1177–083X/08/0301–15  © The Royal Society of New Zealand 2008