Elsevier

Social Science & Medicine

Volume 128, March 2015, Pages 95-104
Social Science & Medicine

Review
Measurement of social capital in relation to health in low and middle income countries (LMIC): A systematic review

https://doi.org/10.1016/j.socscimed.2015.01.005Get rights and content

Highlights

  • Only 21 LMICs have evidence on social capital and health based on primary data.

  • Eighteen different tools have been used in measuring social capital.

  • Cultural adaptation and psychometric validation of tools are recommended.

  • There is scarcity of prospective studies to determine causality.

  • Cognitive dimensions tend to be more associated with health.

Abstract

Social capital is a neglected determinant of health in low and middle income countries. To date, majority of evidence syntheses on social capital and health are based upon high income countries. We conducted this systematic review to identify the methods used to measure social capital in low and middle-income countries and to evaluate their relative strengths and weaknesses. An electronic search was conducted using Pubmed, Science citation index expanded, Social science citation index expanded, Web of knowledge, Cochrane, Trip, Google scholar and selected grey literature sources. We aimed to include all studies conducted in low and middle-income countries, published in English that have measured any aspect of social capital in relation to health in the study, from 1980 to January 2013. We extracted data using a data extraction form and performed narrative synthesis as the measures were heterogeneous. Of the 472 articles retrieved, 46 articles were selected for the review. The review included 32 studies from middle income countries and seven studies from low income countries. Seven were cross national studies. Most studies were descriptive cross sectional in design (n = 39). Only two randomized controlled trials were included. Among the studies conducted using primary data (n = 32), we identified18 purposely built tools that measured various dimensions of social capital. Validity (n = 11) and reliability (n = 8) of the tools were assessed only in very few studies. Cognitive constructs of social capital, namely trust, social cohesion and sense of belonging had a positive association towards measured health outcome in majority of the studies. While most studies measured social capital at individual/micro level (n = 32), group level measurements were obtained by aggregation of individual measures. As many tools originate in high income contexts, cultural adaptation, validation and reliability assessment is mandatory in adapting the tool to the study setting. Evidence on causality and assessing predictive validity is a problem due to the scarcity of prospective study designs. We recommend Harpham et al. s' Adapted Social Capital Assessment Tool (A-SCAT), Hurtado et al. s' six item tool and Elgar et al. s' World Value Survey Social Capital Scale for assessment of social capital in low and middle income countries.

Introduction

In 2005, the WHO Commission for Social Determinants of Health (CSDH) declared that new action strategies addressing social factors are required to improve health of populations, despite provision of equitable health systems (Commision for Social Determinants of Health, April 2007). “Social capital”, was identified as a key determinant of the commissions' framework emphasising its role in creating health equity and wellbeing of individuals and communities (WHO, 2010). This implicates that social capital act both as a structural and intermediary determinant of health. During the past two decades evidence on social capital and health has been frequently synthesized in the attempt to understand its relationship in a broader evidence base (Story, 2013, De Silva et al., 2005, Kawachi et al., 2007, Islam et al., 2006, Uphoff et al., 2013, Vyncke et al., 2013). However, the evidence suggest that the concept has not been a priority concern in Low and Middle Income Countries (LMICs) where inequalities in health are greater than many High Income Countries (HIC) (Story, 2013).

Although social capital is a widely used concept in many fields, there is lack of consensus upon its definition and dimensions. Experts of different fields have contributed to this notion with different viewpoints. In 1986, Pierre Bordieu defined social capital as the “aggregate of the actual or potential resources which are linked to possession of a durable network of more or less institutionalized relationships of mutual acquaintance or recognition” (Bourdieu, 1985). According to Portes this is the most theoretically refined definition for social capital in the sociological discourse (Portes, 1998). However in this discourse, Loury (Loury, 1977), Coleman (Coleman, 1990) and Putnam contributed to develop the distinctions of social capital while Putnams' definition – “features of social organization, such as trust, norms and networks that can improve the efficiency of society by facilitating coordinated actions” (Putnam et al., 1993) – is one of the most widely used in literature. Recently the World Bank defined social capital as the “institutions, relationships and norms that shape up the quality and quantity of a society's social interactions” (The World Bank Group, 2011).

Social capital consists of different dimensions, basically the “structural” and “cognitive” (The World Bank Group, 2011). Structural social capital refers to externally observable social interactions of people (Krishna, 2001, McKenzie et al., 2002, Harpham et al., 2002) whereas cognitive social capital consists of norms, values, and beliefs of people that affect their participation in a society (Islam et al., 2006). The most recent approach (Szreter and Woolcock, 2004) describes social capital in three distinct forms, namely “bonding”, “bridging” (horizontal) and “linking” (vertical) social capital. “Bonding” social capital (also called as localized social capital) refers to interactions between homogeneous members of a community such as family members and close friends and neighbours (De Silva and Harpham, 2007). “Bridging” social capital comprises relations of respect and mutuality between people who know that they are not alike in some socio-demographic sense, such as ethnic or occupational backgrounds (Krishna, 2001). “Linking” social capital, explains the relationships between people across power or authority gradients in a society.

Given social capital is a multifaceted concept (Dasgupta, 2000) underpinned by a long standing sociological discourse, measuring it is a complex procedure. In the first instance, what to measure is a problem. The theoretical views depict that one should measure the structurally observable relationships; cognitive aspects that affect these relationships; access to resources as well as the quality or depth of all these notions. Although numerous approaches have been used, there is no universally applicable gold standard tool to measure social capital. Secondly, operationalizing social capital variables is challenging (Krishna, 2001). Operationalization may vary according to context. The appropriate level at which social capital should be measured remains uncertain. It can be measured at individual (attitudinal and psychological), micro (social networks of individuals), meso (communities) and macro (nations, regions) levels. The current evidence base suggests that the differences in health are better predicted by individual level social capital variables rather than those measured at an ecological level (De Silva et al., 2005). Studies that measure social capital at ecological level lacks appropriate social capital measures which have been an impediment to synthesize evidence (Lochner et al., 1999). Islam et al. suggest that more appropriate statistical measures such as multi-level modelling should be used in understanding the relationship between social capital and health as it can account for the different impacts of individual and ecological level associations (Kawachi et al., 2007).

However, few studies from LMIC have been included in most of the reviews of social capital and health (Story, 2013, De Silva et al., 2005, Kawachi et al., 2007, Islam et al., 2006, Uphoff et al., 2013, Vyncke et al., 2013). Although the concept is considered important as a means of health promotion in LMIC, syntheses of evidence focussing on these countries are scarce (Story, 2013). Furthermore as many of the measures originated in high-income countries (HICs) these may not identify how the concept of social capital is applied and measured in LMIC. Identifying relevant, reliable and valid measurement tools is paramount to understand the impact of social capital in relation to health and its association with health outcomes in developing contexts. As such we conducted a systematic review to identify the methods used to measure social capital in low and middle-income countries and to evaluate their relative strengths and weaknesses.

Section snippets

Methods

A study protocol for the systematic review was prepared according to the guidelines of the Cochrane collaboration (Higgins and SG, 2011).

Results

We retrieved a total of 472 studies by searching the databases and grey literature sources (Table 2). Of these studies, 324 studies were excluded after screening and 46 articles were selected for the review (Fig. 1).

Discussion

This review identifies the variety of measurement used to assess social capital in LMIC and their strengths and weaknesses. We identified that social capital has been measured using both primary and secondary data that are collected through composite and non-composite tools. It is argued in literature that composite measures are better in measuring the concept due to its' multifaceted nature (Lochner et al., 1999). However the variable nature of the associations with health outcomes may mean

Conclusions

We observed that there are many gaps in the measurements of SC in LMICs. Cultural adaptation, validation and assessment of reliability of the tool in the study setting are important in measurement of social capital. Prospective studies are needed to determine the causal relationships between health and social capital as well as to assess predictive validity of the available tools. Of the tools we recommend ASCAT and the six-item scale used by Hurtado et al. to be used in measurement of social

Acknowledgements

Authors would like to acknowledge the financial assisstance provided by the Rajarata University of Sri Lanka under the Grant number RJT/R&P/2012/Med. Alli.Sci./R/01 & RJT/R&P/2013/Med.Alli.Sci/R/06.

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