Elsevier

Social Science & Medicine

Volume 60, Issue 6, March 2005, Pages 1267-1283
Social Science & Medicine

Social capital, geography and health: a small-area analysis for England

https://doi.org/10.1016/j.socscimed.2004.06.050Get rights and content

Abstract

There has recently been much debate about the influence of social capital on health outcomes. In particular it has been suggested that levels of social capital vary from place to place and that such variations may account for previously unexplained between-place variations in health outcomes. As yet few studies exist of the influence of small-area variations in social capital on health outcomes. One reason for this is the difficulty of obtaining indicators for small areas such as electoral wards in England, and we describe a method used to derive what we term ‘synthetic estimates’ of aspects of social capital by linking coefficients produced from multi-level analyses of national survey datasets to census data. We produce estimates for electoral wards in England and apply these in multi-level models of our response variable, the probability of survival of individuals surveyed in the Health and Lifestyle Survey of England. We report various combinations of models incorporating individual attributes, health-related behaviours, area measures of deprivation, and area measures of social capital. Our overall conclusion is that we find little support, at this spatial scale, for the proposition that area measures of social capital exert a beneficial effect on health outcomes.

Introduction

A growing body of research contends that area of residence makes a difference to health-related behaviour and health outcomes (Jones and Moon, 1993; MacIntyre, MacIver & Sooman, 1993). Health outcomes thus depend not only on individual characteristics (age, gender, occupation, etc.) but also on the ‘ecology’, or the surrounding environment in which individuals live and work. The general conclusion which can be drawn from studies of the effect of local social characteristics on health outcomes appears to be that area of residence does have an effect over and above effects of population composition (Pickett & Pearl, 2001; MacIntyre, Ellaway & Cummins, 2002). There is also evidence that area effects vary between places, health outcomes and population groups (Kawachi & Berkman, 2003; MacIntyre & Ellaway, 2003; Robert, 1999).

In searching for explanations of these variations, attention has been directed, through the work of Wilkinson, 1996, Wilkinson, 2001, to the role of the social environment in influencing life chances. Summarising some complex debates, it has been argued that, once a threshold level of development has been reached, it is the more egalitarian societies which have the best health records. Social inequality (especially income inequality) has adverse effects both on individual self-esteem and on community-level social cohesion. Many authors have argued (see the review by Szreter & Woolcock, 2004) that social capital provides a missing causal link between social inequality and health.

Social capital has a long history and many antecedents. The central proposition is that through participation in associational life of various kinds, people become members of groups, which ‘both reflect and help shape identity, norms, beliefs, and priorities’ (Macinko and Starfield, 2001, p. 388). Robert Putnam, perhaps the key contemporary advocate of the concept, defined it as ‘features of social organisation such as networks, norms and trust’ (1993), and Macinko and Starfield (2001, p. 388) suggest that social capital thus refers to ‘available resources (capital) that can accrue to people by virtue of their mutual acquaintance and recognition (social) and that can be used for a variety of productive activities’ (capital). A feature of contemporary analysis is the emphasis on social capital as a property of spatially-defined communities ranging from villages, through regions (Putnam, 1993), to nation-states (Fukuyama, 1995). It is suggested that in communities possessed of high levels of social capital, a number of beneficial outcomes may obtain.

If social capital is generated through various forms of associational activity then there are good reasons to anticipate geographical variations in it (see the review by Mohan & Mohan, 2002). Political participation and volunteerism vary, by age, class, ethnicity and gender (Pattie, Seyd & Whiteley, 2004) and so one would expect compositional effects to produce spatial variations. Interestingly, recent studies (Coulthard, Walker & Morgan, 2002; Williams, 2002) reveal regional variations in voluntary activity which are greater than one would predict on the basis of compositional factors. Other studies suggest a more local dimension to social capital, arguing that the extent and character of civic participation is very much shaped by ‘an appreciation of local issues and problems’, because ‘most people's lives are conducted in the locality in which they reside’ (Parry, Moser & Day, 1992; see also Miller, Timpson & Lessnoff, 1996; Verba, Schlozman & Brady, 1996).

The uneven development of the voluntary sector, which is well-illustrated by the many statistical analyses that have been carried out in the USA (e.g. Wolpert, 1990) and elsewhere (Kendall & Knapp, 1996; Salamon, 1995), may also influence social capital formation. The presence or absence of supportive institutional structures can affect levels of participation and, thereby, influence the formation of social capital (e.g. see Hall, 1999; Maloney, Smith & Stoker, 2000).

Finally, contemporary processes of uneven development may have an impact on the quality of social relationships and, therefore, on levels of social capital. The flight of capital from certain locations has certainly been associated with a decline in civility and increasing levels of crime (Anderson, 1990; Campbell, 1993; Wilson, 1987). This argument implies that there comes a point at which normal social codes in neighbourhoods may break down (Subramanian, Kim & Kawachi, 2002, p. S32). Insofar as the affected neighbourhoods may be relatively small areas, this raises the question of the spatial scale at which social capital operates.

If levels of social capital vary geographically, at what spatial scale ought it to be measured? Putnam does not commit himself on this point although he recently called for more work on subnational variations in social capital (Putnam, 2002). A key problem in developing measures of social capital for areas is that the concept refers to community norms, which cannot easily be measured. Sampson and Raudenbush (1999); see also Sampson, Morenoff and Earls (1999) have pioneered ‘systematic social observation’ of behavioural norms through covert observation of urban neighbourhoods, but these could not easily be extended beyond a small number of areas without vast resources. Researchers have therefore had to resort to measures which correspond to Krishna and Shrader's (2000) distinction between ‘structural’ and ‘cognitive’ components of social capital. The former measures the quantity or quality of associational links or activity, while the latter refers to perceptions of support, reciprocity and trust. Problems of measurement can be illustrated through a consideration of previous studies of the relationship between social capital, place and health.

Kawachi, Kennedy, Lochner and Prothrow-Stith (1997) found statistically significant ecological associations between various aspects of social capital (trust, perceived lack of fairness, perceived helpfulness of others, and membership of groups) and mortality rates for American states. Their analysis suggested that income inequality acted through social capital to influence mortality. Kawachi, Kennedy and Glass (1999) argued, using a multilevel model, that people living in states characterised by low levels of social capital (indexed by measures of trust, reciprocity, and civic engagement) tended to have higher probabilities of lower self-reported health. Even after controlling for individual—level variables (socio-economic characteristics and health-related behaviours) residence in a low social capital area was still associated with an excess risk of reporting fair or poor health. Kawachi, Kennedy and Wilkinson (1999) demonstrated a strong correlation between income inequality, crime and social trust at the state-level, suggesting a link between income inequality and social cohesion. Investigating the Russian mortality crisis, Kennedy, Kawachi, and Brainerd (1998) found that their various indices of social capital and social cohesion were strongly associated with age-adjusted mortality and life expectancy for both men and women. Walberg et al. (1998) also used crime as an index of social cohesion in their regression analysis of regional variations in the fall of life expectancy which occurred after the collapse of communism in Russia. Reductions in life expectancy were most closely associated with labour turnover, and were greatest in regions where crime levels were highest and where incomes were most unequal. Blakely, Kennedy and Kawachi (2001), in a multi-level study, explored the relationship between voting rates and self-rated health in the USA. There was no direct association between income inequality and variations in voter turnout (suggesting that the connection between inequality and this dimension of social capital was not clear) but there was a suggestion that individuals living in states with low voter turnout had increased odds of fair or poor self-rated health.

Subramanian, Kawachi, and Kennedy (2001) investigated the health effects on individuals (measured in terms of the probability of self-reported poor health) of state-level income, income inequality, and social capital. As absolute income increased, the probability of reporting poor health decreased. There were modest effects for income inequality for high-income groups but not for other income groups. Finally, the probability of reporting poor health increased significantly as state-level social capital declined. The authors thus contend that this study demonstrated an ‘independent effect of social capital’ (Subramanian et al., 2001, p. 16).

Some more recent studies have explored relationships at a smaller geographical scale. Lochner, Kawachi, Brennan, and Buka (2003) provided a cross-sectional analysis of the relationship between social capital and mortality for 342 neighbourhood clusters in Chicago. Higher levels of neighbourhood social capital were associated with reduced mortality for Whites, even after adjustment for neighbourhood deprivation. For Blacks, however, the associations were less consistent and often not statistically significant.

Subramanian et al. (2001) found complex effects of community-level social capital on the probability of reporting self-rated poor health in 40 communities in the USA. Higher levels of community social trust were associated with a lower probability of reporting poor health. Controlling for individual-level perceptions of trust, however, rendered the main effect of community-level social trust statistically insignificant. However, there was a complex interaction effect: the health-promoting effects of community-level social trust were apparently greater for high-trust individuals. So, if social capital does have beneficial effects, we cannot assume that it is equally beneficial for all; it ‘may be “good medicine” only for for those who express high levels of trust or who value trustworthiness in others’. Furthermore, once allowance was made for the individual compositional effects of socio-economic status, ‘communities do not make a difference to poor self-rated health’ (Subramanian et al., 2001, p. S31).

The message of these studies is therefore somewhat contradictory. Some strong claims have been made on the basis of ecological analyses for large spatial units, but whether these are units which exert a meaningful influence on peoples lives is debatable. On the other hand, at smaller spatial scales, there is a lack of consistency in the results.

Our work was prompted by the relative absence of similar work on the UK in general and at a small spatial scale in particular. We were struck by an apparent paradox. At the same time as influential studies of health inequality were focussing on small areas, such as electoral wards, work on social capital was being conducted for very large spatial units. There was a need for work which produced estimates of social capital for small areas and then explored whether variations in health outcomes were related to differential levels of social capital.

We first describe how we devised small area estimates of social capital, via a method which we characterise as ‘synthetic estimation’ of aspects of social capital. We then describe a modelling exercise to explore the relationship between individual and area characteristics and health outcomes. The response variable used is the probability that a respondent to the 1985 English Health and Lifestyle Survey (HALS) was still alive in 1999. We seek to explain this in terms of combinations of individual socio-economic attributes, material circumstances of areas, and measures of social capital for small areas. We find that our measures of social capital added little to the explanatory power of our models and we discuss some of the implications of these results.

Section snippets

Creating small-area indicators of social capital: direct measurement and synthetic estimation

Many studies of social capital and health have perforce had to measure their social capital indicators for large spatial units. If we want to develop analyses which are meaningful in relation to the contexts in which people live their lives, however, it is clearly desirable to produce measures of social capital for small areas. If we focus on the structural component of social capital, then there are several possibilities for constructing spatially—disaggregated indicators of the proportion of

Modelling the relationship between social capital, place and health

Our aim was to explore the ecological influence of social capital on individual health outcome. We undertook this task by using the Health and Lifestyle Survey (HALS) which is a comprehensive study of the health of the adult national UK population (Cox, 1988). The original sample from England, Wales and Scotland of 9003 respondents were initially interviewed in 1984/1985 and the original respondents were ‘flagged’ to provide the subsequent date and cause of death (Cox et al. (2001)). The

Conclusions

We have modelled individual and ecological data simultaneously to account for variations in individual mortality in a follow-up study, and in this respect our work contrasts with earlier cross-sectional and aggregate studies. We have been able to assess the effect of individual and ecological measures of social capital in models which also contain demographic, health-related behaviour and social-structural variables at the individual level. Our work is also novel in that we have produced

Acknowledgements

Thanks to the Health Development Agency for funding the work on which this paper was based under their ‘Social capital for health’ programme, and to S. V. Subramanian and Sarah Curtis for their detailed and constructive comments on an earlier version.

References (60)

  • V. Carstairs et al.

    Deprivation and health in Scotland

    (1991)
  • M. Coulthard et al.
    (2002)
  • Cox, B.D. (1988). Health and Lifestyle Survey, 1984–5 computer file Colchester: ESRC Data...
  • Cox, B., et al. (2001). Health and Lifestyle (HALS) Deaths datafile: Second revision, January 2001. Essex University:...
  • R. Cowell et al.

    Backyard and biosphereThe spatial distribution of support for English and Welsh environmental organisations

    Area

    (1995)
  • M. Foley et al.

    Is it time to disinvest in social capital?

    Journal of Public Policy

    (1999)
  • F. Fukuyama

    TrustThe social virtues and the creation of prosperity

    (1995)
  • Gatrell, A., Popay, J., & Thomas, C. (2004). Mapping the determinants of health inequalities in social space: can...
  • W.R. Gilks et al.

    Markov chain Monte Carlo in Practice

    (1996)
  • H. Goldstein

    Multilevel statistical models

    (1995)
  • Goldstein, H., Rasbash, J., Plewis, I., et al. (1998). A User's Guide to MlwiN. Institute of Education, University of...
  • P.A. Hall

    Social capital in Britain

    British Journal of Political Science

    (1999)
  • K. Jones et al.

    Medical geographyTaking place seriously

    Progress in Human Geography

    (1993)
  • Jones, K., Mohan, J., Barnard, S., & Twigg, L. (2004). Mapping the gift relationship: An analysis of the spatial...
  • G. Jordan et al.

    The protest business

    (1997)
  • I. Kawachi et al.

    Social capital and self-rated healthA contextual analysis

    American Journal of Public Health

    (1999)
  • I. Kawachi et al.

    Social capital, income inequality and mortality

    American Journal of Public Health

    (1997)
  • J. Kendall et al.
    (1996)
  • Krishna, A., Shrader, E. (2000). Cross-cultural measures of social capital: A tool and results from Indian and Panama....
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