Questions of trust in health research on social capital: What aspects of personal network social capital do they measure?

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Social Science & Medicine xxx (2014) 1e10

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Social Science & Medicine

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Questions of trust in health research on social capital: What aspects ofpersonal network social capital do they measure?

Richard M. Carpiano*, Lisa M. FittererDepartment of Sociology, University of British Columbia, 6303 Northwest Marine Drive, Vancouver, British Columbia V6T 1Z1, Canada

a r t i c l e i n f o

Article history:Available online xxx

Keywords:CanadaSocial capitalTrustSocial networksTheoryMeasurementSocial determinants of health

* Corresponding author.E-mail address: [email protected] (R.M. Car

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a b s t r a c t

Health research on personal social capital has often utilized measures of respondents’ perceived trust ofothers as either a proxy for one’s social capital in the absence of more focused measures or as a subjectivecomponent of social capital. Little empirical work has evaluated the validity of such practices. We test theconstruct validity of two trust measures used commonly in health research on social capitaldgeneralizedtrust and trust of neighborsdwith respect to measures of people’s general network-, organization-,family-, friend-, and neighborhood-based social capital and the extent to which these two trust measuresare associated with self-rated general health and mental health when social capital measures areincluded in the same models. Analyses of 2008 Canadian General Social Survey data (response rate 57.3%)indicate that generalized trust and trust of neighbors are both positivelydyet modestlydassociated withmeasures of several domains of network-based social capital. Both trust measures are positively asso-ciated with general and mental health, but these associations remain robust after adjusting for socialcapital measures. Our findings suggest that (a) trust is conceptually distinct from social capital, (b) trustmeasures are inadequate proxies for actual personal social networks, and (c) trust measures may only becapturing psychological aspects relevant todbut not indicative ofdsocial capital. Though links betweenperceived trust and health deserve study, health research on social capital needs to utilize measures ofrespondents’ actual social networks and their inherent resources.

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The concept of social capital is credited as one of the mostpopular social science imports into public health (Kawachi, 2010).Since gaining popularity in health researchmore than a decade ago,the application of social capital to studying social determinants ofhealth has resulted in the emergence of two theoreticalperspectives.

The social cohesion perspective, inspired by the scholarship ofColeman (1988) and Putnam (2000), conceptualizes social capitalas the presence of trust, norms of reciprocity, and sanctions avail-able to members of a group for influencing health (Kawachi, 2010).Empirical health research using this perspective often employssurvey measures of perceived trust and reciprocitydto create in-dividual- and community-level social capital indicators (seeKawachi, 2010). By contrast, the network perspective, influenced bythe scholarship of Bourdieu (1986), emphasizes the health impli-cations of actual or potential material, informational, and psycho-social resources rooted within the networks to which individuals

piano).

R.M., Fitterer, L.M., Questionscial Science & Medicine (201

are embedded. Empirical health research using this perspectiveoften utilizes measures of individuals’ social ties and the extent thatthose ties give people potential access to various resources (e.g.,Carpiano and Hystad, 2011; Moore et al., 2009).

Reflecting these conceptual distinctions, some health scholarsstudying personal social capitaldi.e., the social capital that an in-dividual possesses or has access via personal tiesdhave under-standably aimed to be comprehensive in health surveys andincluded measures often categorized into two areas: “cognitivesocial capital,” which refers to people’s subjective values and per-ceptions and is often assessed using, among other items, attitudinalmeasures such as perceived trust of others in general and/or ofone’s neighbors and “structural social capital,”which refers towhatpeople do and is assessed using measures of network ties andgroup/organization participation as well as levels of engagement inreligious and civic activities (e.g., Krishna and Shrader, 1999;Harpham, 2008; Hyyppä and Mäki, 2001; De Silva et al., 2005;Harpham et al., 2002; Ziersch et al., 2005). However, even whenhealth studies are not explicitly aiming to assess cognitive socialcapital, measures of personal trust are the most commonly utilizedmeasures of social capital, with numerous studies reporting

of trust in health research on social capital: What aspects of personal4), http://dx.doi.org/10.1016/j.socscimed.2014.03.017

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R.M. Carpiano, L.M. Fitterer / Social Science & Medicine xxx (2014) 1e102

correlations with health outcomes (Abbott and Freeth, 2008; Kimet al., 2008). These personal trust measures most commonly usedare ones that assess two key conceptual domains of trust: gener-alized trust of others and particularized trust of specific persons,such as neighbors.

Nevertheless, there is a fundamental question that is rarelyacknowledged in health research on personal social capital: Is trustreally social capital? Though health research has often classifiedtrust as a component of social capital and measured it as such,many social capital scholars have presented arguments for a con-ceptual distinction between trust and personal social capital (e.g.,see Portes, 1998; Lin, 2001; Glaeser et al., 2002; Field, 2003).Consistent with these debates, one review of social capitalconcluded that “one cannot assume that social trust is necessarily aproduct of social networks,” calling for further research on thismatter (Policy Research Initiative, 2003, p. 9).

But even if health researchers wish to remain agnostic aboutthese debates and conceptually inclusive in selecting measures, it isimportant to recognize that these conceptual debates constitutemore than academic disagreements of opinion. These concernswith theory translate into important concerns regarding theconstruct validity of measuresdparticularly when health studiesonly utilize trust measures as indicators of personal social capital.At the very least, such debates beg the empirical question: even iftrust measures are simply proxies for social capital when moreprecise measures are unavailable in a dataset, do measures ofperceived trust used commonly in health researchdnamely,generalized trust and particularized trust (of specific people)dadequately capture aspects of a person’s real life social relation-ships (or network ties) and their inherent resources that matter forone’s health? This measurement issue has received little attentionin health research.

The present study aims to contribute to this debate regardingtrust as a measure of personal network social capital. Using Cana-dian national survey data, we evaluate the construct validity of twoperceived trust measures used commonly in health research onsocial capitaldgeneralized trust and trust of neighbors. Specifically,we investigate the extent to which these measures are associatedwith (a) measures of several domains of actual personal socialcapital and (b) self-rated general and mental health once thesesocial capital measures are included in the same models.

1. Background

1.1. Social capital

In evaluating the validity of trust measures as indicators of socialcapital, we explicitly take a position supported by prior scholarshipthat personal social capitaldthe resources that one has access tovia possessing social networksdis conceptually distinct from trust(e.g., Lin, 2001; Field, 2003; Glaeser et al., 2002). Individual socialcapital can exist without trust and possessing trust does notnecessarily mean that one has social capital. Nevertheless, somesocial capital scholarship has included trust as a social capitalcomponent. Below, we provide a brief overview of social capitaltheory, focusing on how key scholars considered trust in relation tosocial capital.

The seminal theoretical scholarship on social capital is typicallyattributed to Bourdieu (1986) and Coleman (1988). Bourdieu (1986,p. 248) defined social capital as:

“the aggregate of actual or potential resources linked topossession of a durable network of more or less institutionalizedrelationships of mutual acquaintance and recognitiondor, inother words, to membership in a group.”

Please cite this article in press as: Carpiano, R.M., Fitterer, L.M., Questionsnetwork social capital do they measure?, Social Science & Medicine (201

By contrast, Coleman (1988, p. S98) proposed that social capitalis:

“defined by its function. It is not a single entity but a variety ofdifferent entities, with two elements in common: they allconsist of some aspect of social structures, and they facilitatecertain actions of actorsdwhether persons or corporateactorsdwithin the structure.

To Coleman, social capital exists in the relations among personsand derives its value from the function of the social structure that,in turn, is the resource that people use to achieve a desiredoutcome.

Both theories consider social capital as resources linked to socialnetworks, but differ regarding what constitutes “resources.”Whereas Bourdieu identifies economic, cultural or symbolic re-sources, Coleman’s resources include trustworthiness of the socialenvironment, obligations, information, norms and effective sanc-tions. Of these two works, only Coleman’s scholarship explicitlymentions the word “trust.” Bourdieu’s thoughts on trust are thesubject of debate (Field, 2002). Nevertheless, Coleman’s more ab-stract social capital definition and inclusion of many processes(some potential antecedents and consequences of social capital)has been argued to be the catalyst for later scholars classifyingmany different concepts under the label “social capital” (Portes,1998).

Coleman’s theory was particularly influential for Putnam (1995,p. 67), who expanded the social capital concept to describe col-lective feature of communities and civic life. Like Coleman, Putnam(1995, p. 67) included different processes under the term “socialcapital,” defining it as “features of social organization, such asnetworks, norms, and social trust, that facilitate coordination andcooperation for mutual benefit.” Though Putnam’s definitionevolved in his later work to subsume trust (i.e., trustworthiness)under the broader conception of norms (Putnam, 2000, p. 19; Field,2002), he reported survey-based trends in generalized trust asevidence for temporal declines in social capital (Putnam, 2000).

Putnam’s theory has particular importance for the present dis-cussion on health research. Other social capital theorists producedwell-citedwork that considered trust as an antecedent, component,or consequence of social capital (see Field, 2002). Putnam’s theory,however, became the most commonly cited within public healthresearch (Moore et al., 2006) and arguably inspired health re-searchers to use perceived trust measures as indicators of socialcapital at not only aggregate (e.g., neighborhood, state) levels ofanalysis (see Kim et al., 2008), but, germane to the present study,the individual level, as either (a) lone indicators of personal socialcapital or (b) components of the cognitive social capitalsubconstruct.

Despite this extensive focus on trust as a component of indi-vidual social capital, Abbott and Freeth (2008, p. 874) contend that,within the health literature, “Trust is usually treated simplistically,both conceptually and in relation to measurement.” Their sugges-tions for overcoming these limitations require attention to the non-health trust literature, which provides important insights aboutwhat different dimensions of trust and their measures maydandmay notdtell us about personal social capital and its relation tohealth (see also Veenstra, 2002).

1.2. Trust and its relationship to social capital

Though discussed and debated as a social capital component,the multidimensional concept of trust has been its own focus ofstudy for several decades across the social sciences. Trust is definedas “the expectation of good will in others” (Glanville and Paxton,


R.M. Carpiano, L.M. Fitterer / Social Science & Medicine xxx (2014) 1e10 3

2007) and is primarily conceptualized in three ways: generalized,particularized, and strategic (Smith, 2013). We focus on generalizedand particularized trust, which are the most commonly used trustconcepts in health research on social capital.

1.2.1. Generalized trustThe conceptualization of trust receiving greatest attention in the

social sciences is generalized trust (see Nannestad, 2008; Smith,2013). Defined as “a belief in the benevolence of human nature ingeneral and thus [.] not limited to particular objects” (Yamagishiand Yamagishi, 1994, p. 139), generalized trust concerns an in-dividual’s evaluation of the trustworthiness of the average personand is not focused on a specific person (Glanville and Paxton, 2007).Thus, it is considered an internal characteristic or disposition anddoes not depend on reciprocity or evidence of another’s trustwor-thiness (Uslaner, 2002; Smith, 2013). Though generalized trust hasbeen theorized to be either innate or learned early in life, evidencehas supported a social learning theory-based explanation (Rotter,1980) of generalized trust, whereby one’s localized experiences oftrust, developed from interactions with specific groups or people,are extrapolated to form one’s generalized trust (Glanville andPaxton, 2007). It is often measured by a standard question askingrespondents, “Generally speaking, would you say that most peoplecan be trusted or that you cannot be too careful in dealing withpeople?” This item has been argued to have decent reliability andvalidity, but debate exists regarding whether it is predictive oftrusting behavior (see Nannestad, 2008; Glaeser et al., 2000;Anderson et al., 2004).

Substantively, generalized trust has been a focus of social sci-ence research because of its hypothesized potential for enablingpeople to connect in political and social spheres with people unlikethemselves (Igarishi et al., 2008; Uslaner, 2002). Such connectionsare analogous to the term “bridging ties” in the social capitalliterature (e.g., Putnam, 2000), which have the potential for facili-tating access to resources outside of one’s in-group. But is gener-alized trust associated with social ties?

For informal social networks, studies have examined types ofties and network structure. Fischer’s (2005) analysis of the 1972e2000 US General Social Surveys revealed that respondent trust ofmost people was (after controlling for age, education, marital sta-tus, and race) only weakly correlated with several common socialcapital indicators, including getting together with neighbors (.04)and friends living outside the neighborhood (.05). For networkstructure, findings from a cross-cultural ego-centric networkanalysis indicated that higher generalized trust was consistentlyrelated to higher density of connectedness among one’s networkmembers (Igarishi et al., 2008). Another ego-centric network study,however, found generalized trust was not associated with having aconfidante to discuss important matters (Moore et al., 2011).

For formal group membership, several studies have reportedpositive associations with generalized trust (Brehm and Rahn,1997; Claibourne and Martin, 2000; Wollebaek and Selle, 2002;Uslaner, 2002; Paxton, 2007). Some of these have also examinedreciprocal associations, finding that the connection from partici-pation to trust was either stronger than the reverse (Brehm andRahn, 1997) or the only direction (Claibourne and Martin, 2000).Nevertheless, some studies have reported rather weak associations(Claibourne and Martin, 2000; Uslaner, 2002; Fischer, 2005)Uslaner (2002) found few associations between generalized trustand 20 measures of civic engagementdof which generalized trustwas reciprocally associated with both charitable and volunteeringacts, while trust influenced business, cultural, and ethnic groupinvolvement.

Overall, this collective evidence suggests that the generalizedtrust measure, while assessing one’s psychological orientation to


the world, does not permit clear assumptions about respondents’informal and formal social network connections and the actual orpotential resources that might be inherent in such tiesdandmatterfor health.

1.2.2. Particularized trustParticularized trust and its measurement concern trust in

specified persons, offering the potential to assess trust of peoplewho are part of one’s “in-group.” Such ties are akin to what issometimes referred to in the social capital literature as “bondingties” (Putnam, 2000), which entail group homogeneity and canpotentially provide exclusive resources to its members. Thoughdistinct from generalized trust (Abbott and Freeth, 2008), particu-larized trust across many life domains is important for shaping aperson’s generalized trust (Glanville and Paxton, 2007).

Health research on social capital, which has a strong focus onlocal communities, often uses measures of personal perceived trustof neighbors (e.g., Fujiwara and Kawachi, 2008; Sapag et al., 2010;Moore et al., 2011). But does this measure capture neighborhoodties? Studies examining associations between trust of neighborsand social capital, though rare, provide some insights. A UK studyfound that trust in neighbors does not necessarily correspond withthe number of neighbors one knows and the frequency that onetalks with neighbors (Coulthard et al., 2002). However, a Canadianstudy found that trust of neighbors was significantly associatedwith having a confidante to discuss important matters located inone’s neighborhood; yet neither measure was directly associatedwith self-rated health (Moore et al., 2011). For formal associations,Kankainen (2009) found that, among a sample of Finns, a person’snumber of association memberships was associated with greatertrust of neighbors (see also Veenstra, 2002). Hence, some evidenceexists that trust of neighbors is associated with social capital.

1.3. Trust in health studies of cognitive and structural social capital

In addition to the abovementioned research on trust, healthstudies examining both “cognitive” and “structural” social capitaloffer the potential for further informing how generalized andparticularized trust correlate with personal network-based socialcapital and health outcomes (as well as other cognitive socialcapital measures like reciprocity). Yet, many of these studies do notreport the correlations between their cognitive and structural so-cial capital measures. Such omissions raise construct validityquestions regarding the extent to which these cognitive andstructural domain-specific measures may actually be capturing thesame underlying latent construct of social capital. However, psy-chometric evaluations conducted across different cultural settingsoffer insights into these issues. Factor analyses of Vietnamese andPeruvian data revealed that generalized trust loaded with othermeasures of cognitive social capital on a single factor, but structuralsocial capital items had very weak loadings on this same factord-thereby suggesting not only very weak correlations betweengeneralized trust and personal network social capital measures, butalso that these items are capturing distinct constructs (De Silvaet al., 2006).

Furthermore, Mitchell and Bossert’s (2007) factor analyses of anextensive range of measures of cognitive and structural socialcapital among respondents living in disadvantaged communities inNicaragua revealed that (a) generalized trust was more highlycorrelated with a factor underlying informal networks (e.g., num-ber of people that could provide actual resources) than it waswith afactor containing numerous measures of particularized trust inspecific persons while (b) trust of neighbors did not produce sub-stantial loadings on any of themodel factors. Therefore, generalized


Table 1Descriptive statistics for dependent and key independent variables (N ¼ 17,769).

N Weighted %

Perceived trustGeneralized trust (people can be trusted) 8611 47.89Trust of neighbors (trust many/most

people in the neighborhood)10,737 57.76

Health outcome variablesVery good/excellent general health 8954 52.26Very good/excellent mental health 10,739 62.08General network social capitalNetwork diversity, mean (SD); weighted mean (SD) 10.09 (4.52) 10.07 (4.45)Any group participation 11,643 65.48Geographic-based social capitalClose relatives in city/local communityNone 5285 28.671e5 9278 52.966e10 2208 12.89Over 10 998 5.48

Close friends in city/local communityNone 2938 16.841e5 10,826 60.796e10 2898 16.46Over 10 1107 5.91

People in neighborhood R knowsNone 809 4.70A few 8352 49.04Many 2541 14.52Most 6067 31.75

People in neighborhood R knows well enough to ask for a favorNone 2208 12.721e5 9611 55.776e10 3240 18.21Over 10 2710 13.30

NOTE: SD ¼ Standard deviation.


trust may be capturing social capital more closely in some contextsthan others.

1.4. The present study

Informed by this prior literature, the present study focuses ontwo issues regarding generalized trust and particularized trust (ofneighbors) measures of personal network social capital. First, iftrust measures are either valid indicators of social capital or simplyproxymeasures for social capital, then our analyses should find that(a) these trust measures are each substantially associated withmeasures of one or more domains of social capital and (b) theirrespective associations with health outcomes weaken substantiallyonce the measures of personal social capital are controlled inmultivariate models.

Second, examining trust of neighbors (as a measure of aparticularized trust) in addition to generalized trust allows usfurther insight into evaluating convergent and discriminant validityof trust as a social capital indicator or proxy. If trust of neighbors ismeasuring social capital, then we should expect this trust measureto correlate more strongly with measures of neighborhood-basedsocial capital than with measures of social capital rooted in moregeneral types of networks.

2. Methods

2.1. Data and sample

We tested these expectations by analyzing data from the 2008Canadian General Social Survey (GSS) Cycle 22, which had a the-matic focus on social networks. The 2008 GSS is a national cross-sectional computer-assisted telephone survey of persons 15 yearsof age and older in all ten provinces of Canada, excluding full-timeresidents of institutions (response rate 57.3%). Specific details of thesampling design have been discussed extensively elsewhere (seeStatistics Canada, 2010).

We limited our analysis to the 19,739 respondents aged 18 orolder, yielding an analytic sample of 17,769 respondents who hadcomplete (non-missing) data for all variables in our analyses. Weuse population-based sampling weights in all our analyses to ac-count for non-response and sampling design (Statistics Canada,2010).

2.2. Measures

Table 1 reports the coding and descriptive statistics for the trust,social capital, and health outcome variables.

2.2.1. Trust measuresWe examine two trust measures. Generalized trust was

measured using a single item asking respondents “Generallyspeaking, would you say that most people can be trusted or thatyou cannot be too careful in dealing with people?” and was coded0 ¼ “You cannot be too careful in dealing with people” and1 ¼ “People can be trusted.” Trust of neighbors was measured usingan item asking respondents whether they trust many of the people,most of the people, a few of the people, or nobody else in theirneighborhood. This variable was coded 0 ¼ nobody/a few in theneighborhood and 1¼many/most people in the neighborhood. Thetetrachoric correlation (rt) between these two trust measures was.53, indicating that they are correlated, but empirically distinct.

2.2.2. Social capital measuresOur social capital measures comprise two domains: general

network social capital, which concerns social capital rooted in a


respondent’s total network and that is not necessarily restricted tosocial ties in a specific locality, and geographic-based social capital,which measures network-based social capital located within therespondent’s city/local community and neighborhood.

2.2.2.1. General network social capital measures. Network diversity,the extent of accessibility that each respondent has to personsoccupying different social positions, was assessed using a positiongenerator (PG)da commonly used social capital instrument in so-ciological research that has also been used in health research (e.g.,Moore et al., 2009; Carpiano and Hystad, 2011). The PG is useful formeasuring general network-based social capital because it samplespositions in a hierarchical (in this case, occupational) structure,rather than sampling interpersonal ties (Lin et al., 2001). Also, thePG in the GSS does not distinguish between family/friends andacquaintances, which enables broad assessment of different tiespossessed by a respondent.

The PG asked respondents if they know someone “by name andby sight and well enough to talk to” in each of 18 different occu-pational positions representing a variety of sectors and occupa-tional prestige levels (e.g., farmer, social worker, police officer orfirefighter, manager in sales, marketing or advertising, computerprogrammer, engineer, delivery or courier driver, nurse, and ac-countants or auditors). Network diversity was computed as the sumtotal of occupational positions for which a respondent reportedknowing someone, thereby ranging from 0 to 18.

Membership/participation in groups was computed as singledichotomous measure (any group membership ¼ 1; no groupmembership ¼ 0) using a series of questions that asked re-spondents if, in the past 12 months, they were a member of orparticipant of a union/professional association; political party/group; sports/recreational organization; cultural, educational orhobby organization; religious-affiliated group; school group,


Table 2Descriptive statistics for sociodemographic and health-related control variables(N ¼ 17,769)d2008 Canadian General Social Survey.

N Weighted %

Male sex 7671 49.24Age18e29 2318 20.8030e44 4665 27.8845e64 7021 35.7365 or older 3765 15.59

EducationLess than secondary graduation 3039 14.95Secondary graduation 2551 14.16Some post-secondary education 2516 15.80Diploma/certificate from communitycollege or trade/technical school

5107 28.21

Bachelor’s or graduate degree 4556 26.88Household incomeLowest 370 1.27Lower-middle 746 3.05Medium 2490 11.88Upper-middle 4975 26.74Highest 6220 40.04Missing income data 2968 17.02

Visible minority status 1435 20.14Aboriginal status 642 3.32Immigrant 2931 20.14Marital statusMarried/common-law 10,575 66.50Divorced/separated/widowed 3693 11.75Single 3501 21.75

Length of residence in neighborhoodLess than 1 year 1262 7.671e5 years 4054 24.105 years to less than 10 years 2905 16.8510 years and over 9548 51.38

Urban (versus non-urban) residence 13,380 81.01Health now compared to 5 years agoWorse than before 5362 28.98Same as before 8232 47.09Better than before 4175 23.93


neighborhood, civic, or community association; service club orfraternal organization; any other group (for which the respondentwas asked to list the total number of other groups). The prevalenceof participation in each group ranged from approximately 3.2% (anyother group) to approximately 30.1% (union/professional associa-tion). Also, due to the potential of membership/participation in a“school group, neighborhood, civic, or community association” toreflect geographically-specific (versusmore geographically-diffuse)ties, we re-computed our dichotomous groupmembership variablewith this specific item excluded. A cross tabulation of the twovariables indicated that they are essentially the same measure.

2.2.2.2. Geographic-based social capital measures. For city/localcommunity social capital, we created two measures that respec-tively focus on the total number of (a) close family and (b) friends inthe respondent’s city/local community whom the respondent feels“at ease with, can talk to about what is on your mind, or call on forhelp.” Both measures were modeled as four dummy variables (1e5,6e10, and over 10, with None as the referent) in order to beconsistent with the neighborhood social capital measuresdescribed below.

Neighborhood social capital was assessed using two items. Thefirst item asked respondents “Would you say that you know most,many, a few or none of the people in your neighborhood?” Wemodeled this response scale as four dummy variables with “none”as the excluded referent category. The second item asked “Abouthow many people in your neighborhood do you know well enoughto ask for a favor?” Examples of favors were “picking up the mail,watering plants, shoveling, lending tools or garden equipment,carrying things, feeding pets when neighbors go on holiday, andshopping.” We modeled its four-point response scale (None, 1e5,6e10, and over 10) as four dummy variables with “none” as theexcluded referent.

2.2.3. Health outcome measuresOur two health outcome variables are self-reported health and

self-reported mental health (hereafter referred to as “generalhealth” and “mental health,” respectively). Each variable is basedon a single item that asked respondents to respectively rate (“ingeneral”) their health and mental health using a five-point scaleranging from “excellent” to “poor.” Both variables were recodedinto separate dichotomous measures where 0 ¼ good/fair/poor andexcellent/very good ¼ 1 and their rt correlation was .72.

2.2.4. Control variablesOur analyses control for an extensive range of sociodemographic

factors and (self-rated) health now compared to five years ago.Table 2 details these items. Household income categories werecomputed using a formula utilized previously in analyses of Cana-dian national data (see Ross, 2002; Carpiano and Hystad, 2011),which accounts for the number of people in the household andproduces five categories coded from “lowest” (the referent cate-gory) to “highest.” We also included a sixth category for re-spondents who had missing household income data. Sensitivityanalyses (not presented here) revealed that this householdmember-adjusted income measure was a stronger predictor ofhealth outcomes than the unadjusted income measure. Further-more, the general pattern of results was the same for analyses thatexcluded cases with missing income data. For urban location, weused the urban/rural indicator in the GSS public use file, whichoriginally coded each respondent’s residential location as: (1)“Large urban centres” (Census Metropolitan Area [CMA]/CensusAgglomeration [CA] Area), (2) Rural and small town (non-CMA/CA),and (3) Prince Edward Island. We recoded this item as 0 ¼ non-urban (categories 2 and 3) and 1 ¼ urban.


2.3. Analyses

Our analyses proceed in two steps. First, we investigate theconvergent and discriminant validity of both trust measures withall personal network-based social capital variables. Because the twotrust measures were substantially correlated, we utilized seeminglyunrelated bivariate probit regression, a multivariate technique thatenabled the joint estimation of generalized trust and trust ofneighbors on the social capital variables. This model consisted oftwo equationsdone for each trust variabledthat specified, as in-dependent variables, the social capital variables as well ascontrolled for sociodemographic and prior health confoundingvariables. The equation for generalized trust also controlled fortrust of neighbors. Due to convergence problems, generalized trustwas not included as a control variable for the equation estimatingtrust of neighbors. Nevertheless, this exclusion is consistent withprior theoretical and empirical research that finds that particular-ized trust is a foundation for generalized trust (Glanville andPaxton, 2007). Also, supplementary analyses (not shown) using abivariate probit model, as well as binary probit and logistic modelsthat controlled for generalized trust revealed results that weresimilar to what are reported here for trust of neighbors.

Second,we investigate thepersonal social capital that potentiallyunderlies the relationship between each trust measure and health.Because this analysis required the inclusion of both correlated trustmeasures as well as the correlated health measures, we utilizedbivariate probit regression to simultaneously estimate equations forboth health outcomes (general health andmental health) in a seriesof models that systematically include the trust and social capital


Table 3Bivariate probit estimates and average marginal effects (marginal probabilities) forgeneral trust and trust of neighbors by social capital variables (N ¼ 17,769)d2008Canadian General Social Survey.

Trust of neighbors Generalized trust

Coeff. Pr(Y ¼ 1) Coeff. Pr(Y ¼ 1)

Social capitalSocial network diversity .016** .005** .013** .005**Any group participation .143** .047** .138** .050**Close relatives in city/local communityNone Referent Referent Referent Referent1e5 .002 .001 -.025 -.0096e10 .066 .021 .007 .002Over 10 .041 .013 .041 .015

Close friends in city/local communityNone Referent Referent Referent Referent1e5 .092** .031** .144** .053**6e10 .269** .088** .387** .142**Over 10 .222** .073** .337** .123**

People in neighborhood R knowsNone Referent Referent Referent ReferentA few .057 .020 .093 .034Many .466** .162** .285** .104**Most .574** .196** .281** .102**

People in neighborhood R knows well enough to ask for a favorNone Referent Referent Referent Referent1e5 .399** .142** .221** .080**6e10 .764** .266** .458** .167**Over 10 .878** .302** .489** .178**

Trust of neighborsNobody/a few in the neighborhood Referent ReferentMany/most people in the neighborhood -.669** -.239**atanh (rho) [standard error] 1.205** [.338]rho .835

*p � .05; **p � .01; NOTE: Both models adjust for the control variables detailed inTable 2. Atanh(rho) is the Fisher’s z transformation of rho, which is the correlation ofthe error terms in the two equations. Atanh(rho) is directly estimated; rho iscomputed as the hyperbolic tangent of atanh(rho) (Buis, 2011).


variables while controlling for sociodemographic factors. Afterpresentingmodels for the association between eachhealth outcomeand (a) each type of trust, (b) both types of trust modeled together,and (c) only the social capital variables,we then estimate fullmodelsto determine the extent to which the initial trustehealth associa-tions remain after controlling for the social capital variables. Diag-nostic analyses (not shown) indicated that therewereno substantialcorrelations between any of the variables that could present po-tential multicollinearity in our analytic models.

Given the complex sampling design of the GSS, we utilizedsurvey weights for all point estimates and computed standard er-rors using the 500mean bootstrap weight variables provided in theGSS dataset (Statistics Canada, 2010). Analyses were conductedusing Stata 13 (StataCorp LP, College Station, Texas). For each in-dependent variable, we report bivariate probit slope estimates, aswell as average marginal effects (AMEs) for the univariate (mar-ginal) predicted probability that a dependent variable equals 1 [i.e.,Pr(Yx ¼ 1)]. Compared to probit coefficients, the AME estimatesbetter facilitate comparisons across models to interpret how muchan initial association increases/decreases once other variables areincluded in these binary outcome models (see Mood, 2010). TheseAMEs can be interpreted as risk differences. For all models, wereport p values �.05 as statistically significant.

3. Results

3.1. Social capital correlates of general trust and trust of neighbors

Table 3 presents results of the seemingly unrelated bivariateprobit model that regresses generalized trust and trust of neighborson the social capital variables while controlling for all confoundingvariables and (for the generalized trust equation) the trust ofneighbors variable.

These results indicate that both trust measures are significantlyassociated to a similar degree of magnitude with both measures ofgeneral network social capital: an approximate risk difference of.5% for each unit increase in network diversity and an approximate5% risk difference for group participation versus no participation.However, the trust measures differ with respect to their correla-tions with other domains. Neither trust variables is significantlyassociated with close family. Close friends living in one’s city/localcommunity shows stronger associations with generalized trust(5.3%e12.3%) versus trust of neighbors (3.1%e8.8%). Allneighborhood-based social capital variables, however, showstronger associations for trust of neighbors (14.2%e30.2%).

Overall, it is important to examine the magnitudes of these es-timates, which collectively indicate that all of the associations forgeneralized trust and the majority of the associations for trust ofneighbors were rather modest. Though both types of trust weresignificantly associated with at least one type of social capital, noprobit estimate exceeded .878dthe association between trust ofneighbors and having 10 or more (versus no) people in one’sneighborhood that one knows well. Furthermore, most probit es-timates were less than .50 (including the highest estimate observedfor generalized trust, which was .489). By comparison, probit esti-mates of .878 and .50 (a) respectively convert to odds ratios (ORs) ofapproximately 4.07 and 2.23 (computed by multiplying the probitcoefficients by 1.6 to convert to logit coefficients [see Amemiya,1981; Gelman, 2006], then exponentiating these products toobtain ORs) and (b) approximate rt correlations of .51 and .31 usingthe equation rt ¼ cos[p/(1 þ OR1/2)] (Bonett, 2007).

Therefore, even though trust of neighbors showed moderatecorrelations with two of the three categories of knowing neighborswell enough to ask a favor (6e10, over 10 people), the collectiveevidence in Table 3 indicates that both trust measures are still


empirically quite distinct from any of the social capital measures.While this is particularly the case for generalized trust, the trust ofneighbors measure demonstrated stronger associations with socialcapital specific to neighborhood versus other group tiesdtherebyindicating greater convergent and discriminant validity (Campbelland Fisk, 1959) with, respectively, social capital measures ofsimilar and dissimilar domains.

3.2. Generalized trust, trust of neighbors, social capital, and health

Next, we examine the extent to which both trust measures co-vary with social capital measures in regression models estimatingthe odds of very good/excellent general and mental health. Table 4shows results for five bivariate probit models that simultaneouslyestimate each health outcome: Models 1 and 2 respectively test thehealth associations for generalized trust and trust of neighbors,Model 3 includes both trust measures, Model 4 tests health asso-ciations for only the social capital variables, and Model 5 includesall trust and social capital variables. All models control for theconfounding factors in Table 2.

For Models 1 and 2, respondents who respectively reportedfeeling that most people can be trusted (versus otherwise) andtrusting many/most (versus nobody/a few) neighbors have signif-icant and, in terms of magnitude, generally similar average mar-ginal risk differences for reporting very good/excellent generalhealth and mental health (approximately 5e7% higher probability).When both trust measures are simultaneously entered into Model3, both trust items are still significantly associated with both healthoutcomes, but their estimates are comparably smaller to thatobserved in the prior models, which can be expected given theircorrelation reported earlier.


Table 4Bivariate probit estimates and average marginal effects for very good/excellent general and mental health by trust and social capital variables (N ¼ 17,769)d2008 CanadianGeneral Social Survey.

1 2 3 4 5

Coeff. Pr(Y ¼ 1) Coeff. Pr(Y ¼ 1) Coeff. Pr(Y ¼ 1) Coeff. Pr(Y ¼ 1) Coeff. Pr(Y ¼ 1)

General healthGeneralized trustCannot be too careful in dealing with people Referent Referent Referent Referent Referent ReferentPeople can be trusted .155** .053** .103** .035** .096** .032**Trust of neighborsNobody/a few in the neighborhood Referent Referent Referent Referent Referent ReferentMany/most people in the neighborhood .200** .068** .165** .056** .112** .037**Social capitalSocial network diversity .007* .002* .006 .002Any group participation .093** .031** .083** .028**Close relatives in city/local communityNone Referent Referent Referent Referent1e5 �.008 �.003 �.007 �.0026e10 �.012 �.004 �.015 �.005Over 10 .086 .029 .083 .028

Close friends in city/local communityNone Referent Referent Referent Referent1e5 .001 .000 �.007 �.0026e10 .053 .018 .029 .010Over 10 .075 .025 .054 .018

People in neighborhood R knowsNone Referent Referent Referent ReferentA few �.037 �.013 �.041 �.014Many .073 .024 .050 .017Most .066 .022 .041 .014

People in neighborhood R knows well enough to ask for a favorNone Referent Referent Referent Referent1e5 .130** .044** .109* .037*6e10 .175** .059** .133* .045*Over 10 .175** .059** .132* .044*

Mental healthGeneralized trustCannot be too careful in dealing with people Referent Referent Referent Referent Referent ReferentPeople can be trusted .186** .066** .137** .048** .129** .045**Trust of neighborsNobody/a few in the neighborhood Referent Referent Referent Referent Referent ReferentMany/most people in the neighborhood .202** .072** .156** .055** .094** .033**Social capitalSocial network diversity .006 .002 .005 .002Any group participation .013 .005 .003 .001Close relatives in city/local communityNone Referent Referent Referent Referent1e5 .042 .015 .043 .0156e10 .097* .034* .095* .033*Over 10 .138* .048* .136* .047*

Close friends in city/local communityNone Referent Referent Referent Referent1e5 .029 .010 .020 .0076e10 .145** .051** .119** .041**Over 10 .132* .046* .108 .038

People in neighborhood R knowsNone Referent Referent Referent ReferentA few .158* .058* .156* .056*Many .252** .090** .232** .083**Most .308** .110** .287** .102**

People in neighborhood R knows well enough to ask for a favorNone Referent Referent Referent Referent1e5 .008 .003 �.012 �.0046e10 .045 .016 .004 .001Over 10 .110* .038* .067 .023

atanh (rho) [standard error] .788** [.019] .786** [.019] .785** [.019] .788** [.019] .784** [.019]rho .657 .656 .655 .657 .655

*p � .05; **p � .01; NOTE: All models adjust for the control variables detailed in Table 2. Atanh(rho) is the Fisher’s z transformation of rho, which is the correlation of the errorterms in the two equations. Atanh(rho) is directly estimated; rho is computed as the hyperbolic tangent of atanh(rho) (Buis, 2011).


Model 4, which examines only social capital variables, indicatesa more divergent pattern of findings across the two health out-comes. For general health, only network diversity, group partici-pation, and knowing people in one’s neighborhood well enough to


ask them for a favor are associated with significantly higher riskdifferences of very good/excellent heath. By contrast, mental healthis significantly associated with having six or more relatives orfriends (versus none) that one feels close to who also live in one’s



city/local community, just knowing an increasing number of peoplein one’s neighborhood, and knowing more than 10 people in one’sneighborhood well enough to ask them a favor.

Model 5, which includes all variables, shows that both trustvariables remain significantly associated with general andmental health once the social capital variables are also includedin the same model. Comparing marginal effects before and aftercontrolling for the social capital variables indicates that theinitial Model 3 marginal effects for generalized trust are onlyreduced by approximately 8.5% for general health and 6.3% formental health. For trust of neighbors, the Model 3 marginaleffects for general and mental health are respectively reducedby 34% and 40%. Collectively, this evidence suggests that, forboth health outcomes, the social capital variables account forsubstantially more of the observed associations for trust ofneighbors than they do for the general trust associations. Also,consistent with the trust findings reported in Table 3, the socialcapital variables that seem to have the most substantial changein estimates from Model 4 to Model 5 are the neighborhood-specific social capital variables. To check the robustness ofthese changes in estimates across models, we conducted sup-plementary analyses (not shown) using the “KHB” method Stataprogram for comparing coefficients between two nestednonlinear probability models (see Kohler et al., 2011). Thoughthis program could not perform the KHB method calculationsfrom the results of bivariate probit models, we instead basedthe calculations on standard probit models for each healthoutcome that simultaneously included both trust measures andwere specified in a similar manner to Models 3 and 5 above. Thepercent change in average marginal effects from those analysesalmost exactly replicated the findings reported here and indi-cated that the degree to which any changes were simply due toscaling differences between models was minimal.

4. Discussion

Forwell over a decade, the voluminous health research literature onsocial capital has commonly utilized attitude-based measures ofgeneralized and particularized trust to measure personal social capital-darguing (when critically evaluated at all) that trust is either a theo-retical component of social capital or, at the very least, a proxymeasurefor actual social capital. Our study evaluated the validity of such claimsfor two commonly used measures of trustdgeneralized trust and trustof neighbors (a formof particularized trust important to examine due tothe common focusonneighborhoodor local communitysocial capital inhealth research). Using a high quality, nationally representative Cana-dian dataset that includedmeasures of several domains of respondents’actual social capital, we find limited evidence for the argument thateither trust measure is a component of or valid proxy for actual socialcapital. In interpreting our findings, we return to the two issues thatmotivated our analyses.

4.1. Analytic issue 1: associations between trust, social capital, andhealth measures

If trust measures are either valid indicators of or simply proxymeasures for social capital, then our analyses should have foundthat (a) these trust measures are each substantially associated withmeasures of one or more domains of social capital and (b) theirrespective associations with health outcomes weakened substan-tially once the measures of personal social capital are controlled inmultivariate models.

We found that both trust measures correlated in the expecteddirections with several domains of social capital measures, but themagnitudes of these relationships were rather modest. Likewise,


the respective relationships that each trust measure had with bothhealth measures (findings previously observed in other studies)remained statistically significant and were only modestly reducedonce the social capital measures were introduced as control vari-ables in the model. Hence, the social capital measures did notsubstantially explain the associations that each trust measure hadwith both general and mental health. When considered together,these findings make it difficult to conclude that perceived trust is acomponent of social capital. At best, these findings provide evi-dence that some social capital domains (a) are associated with thedistinct constructs of generalized trust and trust of neighbors, (b)may mediate the association between these two types of trust andhealth and/or (c) may have indirect influences on health via thesetrust items. Such conclusions are consistent with Lin’s (2001)argument that trust may promote social capital or vice versa aswell as Glaeser et al.’s (2002) rationale for analyzing trust andpersonal social capital separately.

4.2. Analytic issue 2: differential findings for generalized trust andtrust of neighbors

In considering the validity of trust as a social capital indicator orproxy, we proposed that, if trust of neighbors is measuring socialcapital, then we would expect this trust measure to correlate morestrongly with measures of neighborhood-based social capital thanwith measures of social capital rooted in more general network tiesor relationships. Likewise, we would expect the correlation be-tween trust of neighbors and health to be substantially reduced inmagnitude once such neighborhood-based social capital measureswere controlled.

Consistent with this expectation, our findings indicated thattrust of neighbors was more strongly associated with social capitalmeasures focused on neighborhood ties than with measures ofother social capital domains. These findings corroborate prior workthat highlights how particularized trust captures in-group ties orties within one’s community (Uslaner, 2002). Trust of neighborsfocuses on particular people with whom onemay interact regularlyin the conduct of everyday routines and, thus, would be expected tohave less direct application to social capital located beyond one’sneighborhood.

Furthermore, we observed that these associations withneighborhood-based social capital measures (knowing neighbors ingeneral and well enough to ask favors) were substantially strongerfor trust of neighbors than for generalized trust. These findingscorroborate prior research whereby generalized trust had weakassociations with neighbor ties (Fischer, 2005; Moore et al., 2011).

4.3. Summary of collective results

Our findings suggest that these two trust measures arecapturing some construct (or even constructs) that are relatedtodbut conceptually distinct fromdseveral domains of personalsocial capital and, hence, raise questions about the adequacy oftrust measures as proxy measures for personal social capital; thatis, people’s actual social connections or networks and theirinherent resources. As such, these findings are consistent with ar-guments that, while a person’s trust may be representing moraland/or psychological orientations that are relatively distinct fromher/his actual social ties and activities (Uslaner, 2002), it still haspotential health implications (Kawachi et al., 2008).

4.4. Study strengths and limitations

Our study has several strengths. In addition to using highquality, nationally representative survey data, our study was able



to: (a) focus on two measures that respectively captured general-ized trust and particularized trust (in neighbors), (b) include manydomains of personal social capital considered in healthresearchdfrom general networks to more local, geographically-bounded networks, and (c) analyze the data using multivariatetechniques that could better account for the correlations betweenthe trust variables as well as the health variables than could moretraditional binary regression models.

Nevertheless, some limitations need to be considered. First, thesocial capital measures have limitations in terms of precision andthe types of network ties they aim to capture. Likewise, our analysisdid not include measures used in some other social capital studiesincluding participation measures (e.g., hours spent volunteeringand religious service attendance) and behavioral trust measures(e.g., whether respondents leave their doors purposely unlocked)(e.g., Anderson et al., 2004). Given the range of social capitalmeasures we examined though, it is still difficult to argue that therather small reductions in the trustehealth associations producedby these measures are due to the trust measures being strongerproxies for some other types of social capital not included in thisstudy. Second, the cross-sectional nature of our data prevents usfrom making any causal claims. We were able to control for priorhealth status to some degree, but it is still not possible tocompletely rule out that health status may be affecting one’s trustof others and social relationships.

Also, our study only provides evidence about measures of per-sonal social capital. Many health studies examine neighborhood-and country-level social capital, but we are unable to extrapolateour findings to such higher levels of analysis; as doing so risksmaking atomistic fallacies.

4.5. Implications for future health research on social capital

Our findings have important implications for future research.First (and perhaps stating the obvious), health research on socialcapital needs to include measures of people’s actual social capital.Trust exists in many social relationships, but, it is neither a neces-sary nor sufficient factor for the generation of social capital (seeField, 2003; Glaeser et al., 2002). Though one might argue thatgeneralized and particularized trust are capturing the potential orwillingness of a person to establish social ties and generate socialcapital with similar or dissimilar othersdimportant research issuesin their own rightdthis psychological state or disposition to engagewith others is conceptually different from actually possessing socialcapital.

Second, caution should be exercised when using these trustmeasures. While various forms of trust (e.g., generalized, particu-larized) may have health implications via biological, psychological,and sociological pathways, careful attention must be paid to (a)what aspects of trust are specifically being assessed by particularmeasures (essentially, the concordance between constructs andmeasures) and (b) what hypothesized pathways might link a spe-cific trust form to specific health outcomes. For example, general-ized trust may be overlapping with hostilityda personality traitthat has implications for some (stress-related) health outcomes(Kawachi et al., 2008).

Third, studies need to utilize more precise measures of personalsocial capital. Comprehensive efforts to include measures ofcognitive and structural social capital in health surveys (e.g.,Krishna and Shrader, 1999; Harpham, 2008) have been an impor-tant start. However, ego-centric network instruments, such as theName Generator (Moore et al., 2009; Song and Chang, 2012), Po-sition Generator (Carpiano and Hystad, 2011), and ResourceGenerator (van der Gaag and Weber, 2008), offer great utility forcreating measures of social capital that a person can access via


different tiesdand thus can enable greater understanding of hownetworks may facilitate or undermine one’s health.

5. Conclusion

For health research on social capital to make important contri-butions to knowledge, it is essential that researchers utilize mea-sures that capture valid aspects of social capital. While usingperceived trust measures to assess personal social capital may haveappeal due to the lack of more desirable or comprehensive mea-sures in a health dataset (and/or be legitimated in their use basedon prior practices in published studies), authors, peer reviewers,and readers should recognize the conceptual and methodologicalimplications of such practices for making valid inferences.

To be explicit, we are, in no way, arguing for a doctrinaire(arguably anti-intellectual) stance that trust measures should beeliminated from social capital research. As our findings indicate,trust is associated with some domains of social capital. Rather, wesimply stress that the use of trust measuresdlike any othermeasuresdshould be guided by strong theoretical considerationsmotivating one’s research approach (Carpiano and Daley, 2006a,2006b; see also Lindström, 2004). In closing, we stronglyencourage continued theoretical and empirical scrutiny of theconstructs and measures utilized by health researchers in studyingsocial capital as a social structural determinant of health.

Ethics statement

This paper uses publicly available data and thus is exempt fromreview as per the guidelines of the University of British ColumbiaBehavioral Research Ethics Board.

Acknowledgments

Richard Carpiano conducted this research while receivingfunding from Investigator Awards from the Michael Smith Foun-dation for Health Research (_501100000245) and CanadianInstitutes of Health Research (_501100000024). The authorsexpress their thanks to Ralph Matthews, University of BritishColumbia, Thomas Abel, University of Bern, and Jennifer E.V.Lloyd, University of British Columbia for providing scholarshipand/or comments that informed the preparation of thismanuscript, as well as Joy Wang at StataCorp for providingsoftware technical support that enabled the analyses for thispaper. An earlier draft of this paper was presented at the 2013International Conference on Social Stratification and Health,Tokyo, Japan.

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Questions of trust in health research on social capital: What aspects of personal network social capital do they measure?