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doi:10.1016/j.so

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anne.linna@ttl.

Social Science & Medicine 66 (2008) 637–649

www.elsevier.com/locate/socscimed

Social capital at work as a predictor of employee health:Multilevel evidence from work units in Finland

Tuula Oksanena,�, Anne Kouvonenb, Mika Kivimakia,c, Jaana Penttia,Marianna Virtanena, Anne Linnaa, Jussi Vahteraa

aFinnish Institute of Occupational Health, Turku, FinlandbInstitute of Work, Health & Organisations, University of Nottingham, UK

cDepartment of Epidemiology and Public Health, University College London Medical School, UK

Available online 19 November 2007

Abstract

The majority of previous research on social capital and health is limited to social capital in residential neighborhoods

and communities. Using data from the Finnish 10-Town study we examined social capital at work as a predictor of health

in a cohort of 9524 initially healthy local government employees in 1522 work units, who did not change their work unit

between 2000 and 2004 and responded to surveys measuring social capital at work and health at both time-points. We used

a validated tool to measure social capital with perceptions at the individual level and with co-workers’ responses at the

work unit level. According to multilevel modeling, a contextual effect of work unit social capital on self-rated health was

not accounted for by the individual’s socio-demographic characteristics or lifestyle. The odds for health impairment were

1.27 times higher for employees who constantly worked in units with low social capital than for those with constantly high

work unit social capital. Corresponding odds ratios for low and declining individual-level social capital varied between

1.56 and 1.78. Increasing levels of individual social capital were associated with sustained good health. In conclusion, this

longitudinal multilevel study provides support for the hypothesis that exposure to low social capital at work may be

detrimental to the health of employees.

r 2007 Elsevier Ltd. All rights reserved.

Keywords: Finland; Social capital; Self-rated health; Work; Multilevel analysis

Introduction

Social capital, described by Hanifan (1916) as‘‘goodwill, fellowship, mutual sympathy, and socialintercourse among a group of individuals who make

e front matter r 2007 Elsevier Ltd. All rights reserved

cscimed.2007.10.013

ing author. Tel.: +358 30 47 47 544.

esses: tuula.oksanen@ttl.fi (T. Oksanen),

@nottingham.ac.uk (A. Kouvonen),

ttl.fi (M. Kivimaki), jaana.pentti@ttl.fi

ianna.virtanen@ttl.fi (M. Virtanen),

fi (A. Linna), jussi.vahtera@ttl.fi (J. Vahtera).

up a social unit’’ as early as 1916, continues toattract attention in population health research.According to contemporary theorists, such asColeman (1988) and Putnam (2000), social capitalconsists of those features of social organizationwhich act as resources for individuals and facilitatecollective action. These include networks of second-ary associations, high levels of interpersonal trustand the norms of mutual aid and reciprocity.However, there remains controversy, whether thebenefits of social capital accrue to individuals or

.

ARTICLE IN PRESST. Oksanen et al. / Social Science & Medicine 66 (2008) 637–649638

groups (Kawachi, Kim, Coutts, & Surbamanian,2004). Furthermore, it not clear whether socialcapital is a resource of individuals or communities.Taking into account that ecological studies havefound associations between social capital andhealth, it is difficult to distinguish between composi-tional (i.e. individual) and contextual (i.e. group)effects of social capital on health. (Poortinga,2006a). Thus, it has been suggested that thepreferred unit of analysis for conceptualizing andmeasuring social capital is both an individual andecological one (Szreter & Woolcock, 2004).

While studies in this field have traditionallyfocussed on social capital in residential or geogra-phical areas, it has now been suggested that socialcapital at work should also be targeted (Baum &Ziersch, 2003; Kawachi, 1999). The workplace mayconstitute an important social unit in this respectbecause many people spend more waking hours atwork than elsewhere, and workplace is a significantsource of social relations. Compared to largegeographic units, like states, workplaces might moreappropriately capture the important social interac-tions and networks that constitute the core of socialcapital (Sundquist & Yang, 2006). Indeed, civicengagement and social connectedness can befound inside the workplace, not only outside of it(Putnam, 2000).

Analyses taking into account the multilevelstructure of data comprising individuals in socialunits have been a major advancement in socialcapital research (Szreter & Woolcock, 2004; Yen &Syme, 1999). These techniques enable the inclusionof predictors at multiple levels and provide a flexibleframework to examine not only group leveldifferences (within and between groups), attributa-ble to either contextual differences or compositionaleffects, but also interaction between variables ofdifferent levels. To date, several studies haveexamined social capital and self-rated health amongworking age population in a multilevel setting. Moststudies have documented an association betweenhigher social capital and better self-rated health ateither individual level or aggregate level (Browning& Cagney, 2002; Franzini, Caughy, Spears, &Fernandez Esquer, 2005; Islam, Merlo, Kawachi,Lindstrom, & Gerdtham, 2006; Kavanagh, Bentley,Turrell, Broom, & Subramanian, 2006; Kavanagh,Turrell, & Subramanian, 2006; Kawachi, Kennedy,& Glass, 1999; Kim & Kawachi, 2006; Kim,Subramanian, & Kawachi, 2006; Lindstrom, Mo-ghaddassi, & Merlo, 2004; Poortinga, 2006a, 2006b;

Subramanian, Kawachi, & Kennedy, 2001; Sub-ramanian, Kim, & Kawachi, 2002; Sundquist &Yang, 2006; Veenstra, 2005; Wen, Browning, &Cagney, 2003). In addition, some multilevel studieshave reported a cross-level interaction with mod-ifications of the effects of individual-level socialcapital by community-level social capital (Kim &Kawachi, 2006; Poortinga, 2006a; Subramanianet al., 2002). However, none of these studiesspecifically focussed on social capital at workplace.Furthermore, the cross-sectional study designsemployed in previous studies prevented evaluationof the temporal order between exposure andresponse.

Given the limitations in previous research, itremains unclear whether social capital represents aconsequence or an antecedent of health and howchanges in individual or work unit social capitalinfluence health. In the present study, we long-itudinally examined the associations between socialcapital at work and change in social capital withhealth impairment among employees. To take intoaccount the fact that individual employees arenested in social units comprised of work units, weused multilevel modeling.

Methods

Participants and study design

Data were derived from the Finnish 10-Townstudy, an on-going prospective cohort study explor-ing the relationships between behavioral andpsychosocial factors and health among local gov-ernment employees (Kivimaki, Vahtera, Elovainio,Virtanen, & Siegrist, 2007). The Ethics Committeeof the Finnish Institute of Occupational Healthapproved the study. In 2000–2001, 32,299 full-timepermanent or fixed-term employees aged 17–64years responded to a postal survey on social capitaland health (response rate 67%). Of them, 24,196were still contracted to the towns at the time of thefollow-up survey in 2004, and 19,077 responded(response rate 79%). The respondents were linkedto their work units on the basis of register dataobtained from the municipalities. The register datainclude the beginning and end dates of the jobcontract, type of job contract and occupational titleby work unit, updated annually.

To study incident impairment in health at follow-up participants with poor self-rated health atbaseline were excluded (n ¼ 5114). In addition, we

ARTICLE IN PRESST. Oksanen et al. / Social Science & Medicine 66 (2008) 637–649 639

excluded 729 individuals due to missing data onhealth or social capital in either survey and 207employees working in units with less than threeemployees, because social capital is only accumu-lated in groups. We further excluded those whohad changed work unit between 2000 and 2004(n ¼ 3654) to be able to assess more accurately theaccumulation of social capital within work units.Thus, the final cohort of this study included 9524initially healthy employees, who worked in a total of1522 work units (e.g. school, kindergarten, hospitalward). The delineation of the study sample byvarious exclusions is shown in Fig. 1.

The sample did not substantially differ from theinitially healthy eligible population (i.e. all healthypersons employed in the 10 towns in 2004) in termsof mean age (44.2 years in the sample, 43.6 years inthe eligible population), the proportion of women(79% vs. 78%), occupational status (14% manual,86% non-manual vs. 15% manual, 85% non-manual) and mean individual-level social capital atbaseline (3.69 vs. 3.69).

Dependent variable

Self-rated health was used to measure health. Therespondents made an assessment of their currenthealth using a five-point Likert scale (1 ¼ verygood, 2 ¼ good, 3 ¼ average, 4 ¼ poor, 5 ¼ verypoor). Self-rated health is one of the most widelyused measures of health status (Krause & Jay,1994), shown to be related to a number of importantmedical endpoints (Idler & Benyamini, 1997; Idler,Russell, & Davis, 2000; Kivimaki et al., 2003) andsensitive to changes in health status (Bailis, Segall,& Chipperfield, 2003; Idler et al., 2000). As in earlierresearch (Idler et al., 2000; Kivimaki et al., 2007),this measure was dichotomized and ratings of verygood and good were combined as ‘‘good’’ while theratings average or worse were combined as ‘‘poor’’.

Independent variable

Social capital at work was assessed with avalidated and psychometrically tested measure,described in detail elsewhere (Kouvonen et al.,2006). In brief, this scale taps both the cognitive andstructural components of social capital at work aswell as the three types of social capital: bonding,bridging and linking (Harpham, Grant, & Thomas,2002; Krishna & Shrader, 1999; Woolcock &Narayan, 2000). The scale measures shared attitudes

and values among members of a work unit,reciprocity, mutual respect and trust between work-mates, collective action and participation in thenetworks at work, and trust in and trustworthinessof a supervisor.

The measure is constructed of eight items: ‘‘Wehave a ‘we are together’ attitude’’, ‘‘People feelunderstood and accepted by each other’’, ‘‘Peoplekeep each other informed about work-related issuesin the work unit’’, ‘‘Members of the work unit buildon each other’s ideas in order to achieve the bestpossible outcome’’ ‘‘People in the work unitcooperate in order to help develop and apply newideas’’, ‘‘We can trust our supervisor’’, ‘‘Our super-visor treats us with kindness and consideration’’,and ‘‘Our supervisor shows concern for our rights asan employee’’. This eight-item scale has been shownto be a reliable and valid measure of social capital(Kouvonen et al., 2006). The responses were givenin a five-point scale (1 ¼ totally disagree, 5 ¼ totallyagree). We used the mean of these eight ratings. Ahigh score indicates high individual-level socialcapital. The internal consistency of this measure-ment was good (Cronbach’s alpha ¼ 0.87).

An independent aggregated social capital of thework unit (second level) was calculated as the meanof individual (first level) responses from co-workersin the same work unit. Thus, work unit socialcapital score was assessed independently of therespondent’s own score, i.e. self-estimation was nottaken into account. This work unit-level socialcapital score was then linked to the respectivemember of the work unit. All work unit-level scoresof social capital were based on at least two co-workers’ responses, because work units with lessthan three respondents were excluded from theanalysis.

The individual-level and work unit-level socialcapital were assessed at baseline and follow-up. Thedistribution of individual-level social capital atbaseline (divided into eights) in relation to poorself-rated health at follow-up showed that theproportions of participants with poor self-ratedhealth in the four lowest levels of social capital weresignificantly higher than their share in the fourhighest groups (the proportions of participantsfrom the lowest level to the highest: 24.1%,19.2%, 16.5%, 19.1%, 15.5%, 15.6%, 14.9% and15.9%). Because of this non-linear association, weused median score as a cut point to dichotomizethe social capital variables into high and low atbaseline and at follow-up, for both levels of analysis.

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FINAL COHORTInitially healthy participantswith full information on social capital,health and work unit characteristicswho remained in the same work unitbetween 2000 and 2004

n= 9524

Excluded if non-identifiablen= 565 (63)

Excluded if missing survey dataon social capital in either surveyor health in 2004

n= 729

Excluded if not employed in theTen Towns in 2004

n= 7538 (66)

Excluded if not responded tosurvey in 2004

n= 5119 (70)

Excluded if poor self-rated healthat baseline in 2000

n= 5114

Excluded if size of work unitpersonnel < 3

n= 207

Excluded if work unit changedbetween 2000 and 2004

n= 3654

Employees of the Ten Towns in 2004who responded to both surveysin 2000 and 2004

n= 19 077 (73)

Employees of the Ten Townswho responded to the survey in 2000

n= 32 299 (70)

Fig. 1. The delineation of the follow-up study sample by various exclusions (percentages of initially healthy).

T. Oksanen et al. / Social Science & Medicine 66 (2008) 637–649640

Then the study sample was divided into four groupsaccording to the levels of social capital at baselineand follow-up, i.e. having low and low, high andlow, low and high, or high and high levels ofsocial capital at the baseline and follow-up stages,respectively. These categories were considered re-presenting different exposure to individual-level andwork unit level social capital (Kawachi & Subrama-nian, 2006).

Assessment of individual characteristics

Most of the baseline characteristics of theparticipants were obtained from survey responses.Marital status was assessed as married or cohabitingvs. single, divorced or widowed. Smoking status wasmeasured with a dichotomous variable describingcurrent regular and daily smoking (current vs.never- or ex-smoker). Alcohol use was based on

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the respondents’ report of their habitual frequencyand amount of beer, wine and spirits intake. Thisinformation was transformed into grams of absolutealcohol per week (Vahtera, Poikolainen, Kivimaki,& Ala-Mursula, 2002). Responses were classifiedinto two categories: no to moderate (o210 g/wk) vs.heavy drinking (X210 g/wk) (Rimm, Williams,Fosher, Criqui, & Stampfer, 1999). Physical activity

was expressed in Metabolic Equivalent Task (MET)hours per day. Participants reported the averageamount of time spent per week in physical activitycorresponding to the activity intensity of walking,vigorous walking, jogging and running. The timespent at each activity in hours per week wasmultiplied by its typical energy expenditure ex-pressed in METs. Physical activity was assessed asthe score of leisure MET hours per day and used asa binary variable (less than 2 MET hours per day vs.more) (Kujala, Kaprio, Sarna, & Koskenvuo, 1998).Body mass index (BMI) was calculated from self-reported weight (kilograms) divided by height(meters) squared and used to form three groups:normal body weight (BMI o25), overweight (BMI25–29) and obesity (BMI X30) (World HealthOrganisation, 2000).

The following information was derived from theemployers’ records: sex, age and occupational statusbased on International Standard Classification ofOccupations (ISCO-88) (Statistics Finland, 2001).The participants were divided into four groups:classes 1 and 2 combining managers and profes-sionals, class 3 denoting associate professionals,classes 4 and 5 combining clerks and serviceworkers, and classes 6–9 manual workers.

Assessment of work unit level variables

Based on work unit identification codes andinformation of the beginning and end dates of alljob contracts in 2004, we calculated the totalworking hours (person-years) in each work unit tomeasure the following work unit characteristics: size(the number of employees), mean age of employees;the proportion of total working hours done by men,by temporary employees and by manual employees.All these second level characteristics were treated ascontinuous variables in the analyses.

Statistical analysis

Multilevel logistic regression analyses (MLRA)were used to model effects of individual level

(compositional) and work unit level (contextual)determinants on health in a hierarchical context.Multilevel models take into account the existence ofdata hierarchies by allowing for residual compo-nents at each level in the hierarchy and simulta-neous examination of the effects of group level andindividual level variables on individual level out-come while controlling for the non-independence ofobservations within groups (Goldstein, 1995). Inmultilevel logistic regression analysis, it is assumedthat both individuals and work units are randomlysampled, and that there is independence betweenindividual and work unit residuals. All statisticalanalyses were performed with SAS 9.1.3 statisticalsoftware (SAS Institute, Inc., Cary, NC) applyingthe Glimmix-procedure.

First we estimated a model which included only arandom intercept and allowed us to detect theemergence of a possible contextual dimension forsocial capital. We used intra-class correlation (ICC)to study the differences of variance in social capitalbetween work units. ICC offers information aboutthe resemblances of individual responses withinwork units and can be used to justify the imple-mentation of this concept as a contextual phenom-enon (Diez Roux, 2002). A possible clusteringwould indicate that work units have specialinfluence on social capital, which in turn wouldjustify the use of the ecological measure (Bryk &Raudenbush, 1992). ICC was 22% indicating thesignificant variance of individual social capitalbetween work units.

We also used rwg (within-group agreement index)to measure the variability of individual responses.rwg is calculated by comparing an observed groupvariance with an expected random variance (James,Demaree, & Wolf, 1984). A high rwg would furtherindicate that social capital may be treated as acontextual phenomenon and give support to theaggregation of unit members’ perception of aphenomenon to form a derived variable. The rwgof social capital in work units was 0.87. An rwg rateabove 0.7 supports the homogeneity in the percep-tions of the phenomenon.

We also counted the variance components (ran-dom effects) of self-rated health at follow-up in allmodels of individual level and work unit level socialcapital to estimate the work unit level variance inthe change of health after baseline (Datta et al.,2006).

The associations of baseline levels of individualsocial capital with individual characteristics were

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studied with analysis of variance. We used repeatedmeasures analysis of variance to examine thedifferences in trends between mean levels ofindividual social capital at baseline and at follow-up. The associations between different levels ofexposure to either individual level or work unit levelsocial capital and health impairment were examinedwith multilevel logistic regression analyses. First weestimated the association between exposure todifferent individual levels of social capital and self-rated health. Adjustments were made for first levelcovariates. We then repeated the analyses with workunit social capital and estimated how work unitsocial capital was associated with possible change inindividual health. Adjustments were made forsecond level covariates. The group with high tohigh levels of social capital was set as the referencegroup in all analyses. We expressed the results asodds ratios (OR) and their 95% confidence intervals(95% CI). In addition to the main effects, we alsostudied interactions by adding respective terms(sex� social capital and occupational status� socialcapital) in the models and analyzed the cross-levelinteraction between individual level and work unitsocial capital. Finally, we studied the effect ofindividual and work unit level social capital onhealth in work units characterized with an increas-ing proportion of manual work.

Results

As shown in Table 1, the study sample comprisedmostly of women (79%), who also reported havingstatistically more individual level social capital atbaseline than men (po0.0001): the mean was 3.71(S.D. 0.72) for women and 3.59 (S.D. 0.72) for men.In relation to occupational status, manual workersrepresented the smallest occupational group (14%)in the sample and they also reported the lowest levelof individual social capital at baseline. The meansocial capital was 3.57 (S.D. 0.77) for manualworkers and 3.73 (S.D. 0.70) for managers andprofessionals. The differences between occupationswere statistically significant (po0.0001). Of otherindividual characteristics, only alcohol use wasassociated with the accumulation of social capital.

In general, the mean of individual-level socialcapital at work decreased slightly during the 4-yearfollow-up from 3.69 (S.D. 0.72) to 3.67 (S.D. 0.73).While there was no difference in trend betweensexes, the difference in trend between occupationalgroups was statistically significant. Among occupa-

tions, the highest decrease was seen in manualworkers. In addition, the level of social capitalamong the single, divorced or widowed decreasedsignificantly compared with the married or cohabit-ing. Also ex- and never-smokers reported a declinein individual social capital during the study period.

Table 2 shows the characteristics of the workunits in 2004. The size of personnel in the workunits varied from 3 to 746, and the mean size of awork unit was 80 people. However, 63% of thepersonnel were in units with less than 50 employees.In 30% of the work units, the share of temporaryworkers was 30% or more at the time of the follow-up. Only 16% of the work units consisted of femaleworkers only. Of the work units 37% comprised nomanual workers, and in 15% the percentage ofmanual workers exceeded 50% (data not shown).

Individual level social capital

Table 3 shows that constant low (low to low) anddeclining (high to low) levels of individual socialcapital were associated with an increased risk ofhealth impairment at 4-year follow-up in initiallyhealthy participants: the odds ratios compared withthe reference group (constant high levels) were 1.78(95% CI 1.56–2.03) and 1.56 (95% CI 1.34–1.86),respectively. Conversely, an increase in individual-level social capital over time (low to high) wasassociated with no extra risk of health impairment(OR 1.07, 95% CI 0.89–1.28). Further adjustmentfor other individual characteristics did not attenuatethe findings. We found no evidence of interactionbetween sex and social capital (p ¼ 0.51) oroccupational status and social capital (p ¼ 0.20)and subgroup analyses showed that these findingswere replicable in men and women and across alloccupational groups (data not shown).

Table 3 also shows all the ORs for healthimpairment related to socio-demographics andhealth risk behavior. There was a graded associationbetween occupational status and poor health, therisk being the highest in manual workers. A risk ofhealth impairment was also related to increasingage, current smoking, physical inactivity and abovenormal BMI. Multilevel modeling revealed that thework unit level variance in health decreased with theaddition of individual level variables (Model 2)from 0.019 to 0.010. The difference in healthbetween work units attenuated to non-significant(p ¼ 0.055) indicating that individual factors ex-plain much of the variation of health in work units.

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Table 1

Baseline characteristics and individual-level social capital for initially healthy participants (N ¼ 9524)

Individual characteristic N (%) Social capital at baseline

mean (S.D.)

Social capital at follow-

up mean (S.D.)

Difference in

trend, p

All 9524 3.69 (0.72) 3.67 (0.73)

Sexa 0.10

Male 2036 (21) 3.59 (0.72) 3.55 (0.74)

Female 7488 (79) 3.71 (0.72) 3.70 (0.73)

Age (mean, S.D.) 44.2 (8.1) – –

Occupational statusa 0.03

Managers and professionals 3640 (39) 3.73 (0.70) 3.72 (0.72)

Associate professionals 1322 (14) 3.61 (0.72) 3.59 (0.74)

Clerks and service workers 3167 (33) 3.72 (0.71) 3.71 (071)

Manual workers 1316 (14) 3.57 (0.77) 3.50 (0.79)

Married or cohabiting 0.008

No 2205 (23) 3.67 (0.73) 3.62 (0.76)

Yes 7234 (77) 3.69 (0.72) 3.69 (0.73)

Smoking status 0.004

Current 1621 (17) 3.69 (0.71) 3.68 (0.72)

Ex- or never-smoker 7664 (83) 3.69 (0.75) 3.63 (0.77)

Alcohol usea (g/wk) 0.11

Heavy (X210) 863 (9) 3.58 (0.75) 3.60 (0.75)

Moderate or less (o210) 8614 (91) 3.70 (0.72) 3.68 (0.73)

Physical activity (MET hours per day) 0.80

o2 h 1996 (21) 3.65 (0.73) 3.63 (0.75)

X2 h 7501 (79) 3.70 (0.72) 3.68 (0.73)

Body mass index 0.69

Normal (o25) 5706 (61) 3.70 (0.71) 3.69 (0.73)

Overweight (25–29) 2873 (30) 3.68 (0.73) 3.66 (0.74)

Obesity (X30) 820 (9) 3.63 (0.74) 3.61 (0.74)

aAssociation with individual level social capital at baseline significant (po0.0001).

Table 2

Characteristics of the work units (N ¼ 1522) at follow-up

Mean proportion of temporary workers 23.0 (14.7, 0–100)

Mean proportion of men 23.8 (27.5, 0–100)

Mean proportion of manual workers 18.8 (26.8, 0–100)

Mean age of the employees 44.6 (3.2, 30.7–56.9)

Mean size 80.2 (121.4, 3–746)

Figures are means (S.D., range).

T. Oksanen et al. / Social Science & Medicine 66 (2008) 637–649 643

Work unit level social capital

We further examined whether work unit level (co-workers’ assessed) social capital has a contextualeffect on the risk of health impairment. Table 4shows the effects of different exposure to work unitsocial capital on individual health. In Model 1,constant low levels (low to low) of social capital in

the work unit predicted an adverse change in thehealth of initially healthy participants working inthese units: the odds for poor health was 1.27 (95%CI 1.10–1.45) compared with those in work unitswith constant high work unit social capital. Whenindividual socio-demographics and lifestyle wereadded in the Model 1, the OR for poor health was1.19 (95% CI 1.03–1.37) indicating that the effect ofwork unit social capital on health was notaccounted for by individual factors (data notshown). However, if second level variables wereadded in the model (Model 2), the risk of healthimpairment in work units with constant low levelsof work unit social capital attenuated to a non-significant level, OR was 1.14 (95% CI 0.99–1.32).The variance at work unit level decreased to non-significant first after the addition of second levelvariables (p ¼ 0.074), indicating that the contextual

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Table 3

Individual-level social capital and the risk of health impairment

Variable Empty

model

Model 1

(unadjusted),

OR (95% CI)a

Model 2

(adjusted)b, OR

(95% CI)a

Fixed effects

Individual social capital

Low–low 1.78 (1.56–2.03) 1.97 (1.65–2.36)

High–low 1.56 (1.34–1.86) 1.86 (1.49–2.33)

Low–high 1.07 (0.89–1.28) 1.19 (0.92–1.54)

High–high 1.00 1.00

Age: 10 years 1.36 (1.27–1.47)

Sex

Women 1.00

Men 0.84 (0.71–1.00)

Occupational status

Managers/

professionals

1.00

Associate

professionals

1.11 (0.93–1.34)

Clerks/

service

workers

1.24 (1.08–1.43)

Manual

workers

1.85 (1.56–2.19)

Marital status

Married or

cohabiting

1.00

Other 1.08 (0.95–1.23)

Smoking status

Ex-or

never-smoker

1.00

Current 1.20 (1.04–1.38)

Alcohol use

Moderate

or less

1.00

Heavy 1.12 (0.93–1.36)

Physical activity

X2 MET

hours per

day

1.00

o2 MET

hours per

day

1.38 (1.22–1.58)

Body weight

Normal 1.00

Overweight 1.41 (1.25–1.60)

Obesity 1.95 (1.63–2.33)

Random effects

Work unit

variance (S.E.)

0.021 (0.006) 0.019 (0.006) 0.010 (0.005)

p-Value 0.0003 0.0008 0.07

aOdds ratios (OR) with 95% confidence intervals (CI) for poor

self-rated health after inclusion of individual-level variables.bAll variables adjusted for each other in the model.

T. Oksanen et al. / Social Science & Medicine 66 (2008) 637–649644

characteristics of the work units explain the varia-tion of the effects of work unit social capital onhealth. We found no evidence of interactionbetween sex and work unit social capital(p ¼ 0.54) or occupational status and work unitsocial capital (p ¼ 0.32).

We conducted additional analyses to examinewhich of the characteristics of the work unitexplained the observed attenuation of the effect ofwork unit social capital on health. After the one byone inclusion of each of the second level variables inthe model, we discovered that the attenuation of therisk to a non-significant level was accounted for bythe proportion of manual workers in the work units.Inclusion of the proportion of manual workers inthe model attenuated the OR by 48% from 1.27(95% CI 1.10–1.45) to 1.14 (95% CI 0.99–1.30).Other second level variables attenuated the OR onlyby 11–26% and the risk remained statisticallysignificant. In order to gain a more profoundunderstanding of this contextual effect, we dividedthe work units into three groups based on theproportion of manual workers using Q1 and Q3 ascut points. Table 5 shows that constantly low workunit social capital was associated with a 1.5-fold riskof health impairment in work units characterized bya high proportion of manual workers. Interestingly,this effect remained essentially the same even aftercontrolling for individual occupational status (OR1.41, 95% CI 1.04–1.91). In addition, there was noextra risk of deterioration of health associated withcontinuous low levels of work unit social capital inthe work units where the proportion of manualworkers was lower or nil. A corresponding findingwas observed also in relation to individual socialcapital: the highest ORs for health impairment werein the work units with the highest proportion ofmanual workers. The risk, however, emerged also inwork units with less or no manual workers.

Discussion

This longitudinal study of 9524 initially healthyemployees in 1522 work units supports the status ofsocial capital at work as a predictor of health.Individual level analysis showed that both aconstantly low level of social capital and a declinein social capital were associated with the impair-ment of self-rated health. An increase in individual-level social capital from low to high was associatedwith sustained good health. These results were notattributable to participants’ socio-demographic

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Table 4

Work unit-level social capital and the risk of health impairment

Variable Empty model Model 1 (unadjusted),

OR (95% CI)aModel 2 (adjusted)b,

OR (95% CI)a

Fixed effects

Work unit social capital

Low–low 1.27 (1.10–1.45) 1.14 (0.99–1.32)

High–low 1.01 (0.84–1.21) 0.99 (0.82–1.19)

Low–high 1.12 (0.94–1.34) 1.08 (0.91–1.29)

High–high 1.00 1.00

Proportion of temporary workers (30% increase)c 1.22 (1.06–1.39)

Proportion of men (30% increase)c 0.96 (0.89–1.03)

Proportion of manual workers (30% increase)c 1.30 (1.21–1.39)

Mean age (10 years increase)c 1.38 (1.12–1.70)

Work unit size (10 person-years increase)c 1.00 (0.99–1.01)

Random effects

Work unit variance (S.E.) 0.021 (0.006) 0.019 (0.006) 0.010 (0.005)

p-Value 0.0003 0.0008 0.074

aOdds ratios (OR) with 95% confidence intervals (CI) for poor self-rated health after inclusion of work unit-level variables.bAll variables adjusted for each other in the model.cOR for the increase in the predictor variable.

Table 5

Social capital and the risk of health impairment by work unit socioeconomic structure

Social capital 2000 and

2004

Proportion of manual workers in the work unit

0% (N ¼ 3492) 1–23% (N ¼ 3671) 24–100% (N ¼ 2361)

OR (95% CI)a OR (95% CI)a OR (95% CI)a

Individual-level

Low–low 1.56 (1.25–1.95) 1.75 (1.42–2.16) 2.21 (1.71–2.87)

High–low 1.23 (0.91–1.67) 1.62 (1.25–2.08) 2.22 (1.61–3.07)

Low–high 0.91 (0.66–1.26) 0.85 (0.63–1.56) 1.74 (1.24–2.44)

High–high 1.00 1.00 1.00

Work unit-level

Low–low 1.07 (0.85–1.35) 1.10 (0.87–1.38) 1.52 (1.13–2.05)

High–low 0.81 (0.59–1.11) 1.23 (0.93–1.63) 0.97 (0.67–1.40)

Low–high 1.11 (0.82–1.49) 1.01 (0.76–1.33) 1.23 (0.85–1.79)

High–high 1.00 1.00 1.00

aAll models adjusted for age and sex.

T. Oksanen et al. / Social Science & Medicine 66 (2008) 637–649 645

characteristics or lifestyle. Importantly, we alsofound a contextual effect of work unit social capitalon health. Constant low levels of social capital inthe work unit, as assessed by co-workers, wereassociated with the risk of poor health that was notaccounted for by individual characteristics.

To our knowledge, this is the first multilevelmodeling study that prospectively examined theassociation between social capital at work and self-rated health. Previous multilevel studies have shown

that the risk of poor health is related to low socialcapital assessed either at individual level (Lindstromet al., 2004; Poortinga, 2006a; Veenstra, 2005) or ataggregated level derived from individual responsesmeasured from same (Franzini et al., 2005; Kava-nagh et al., 2006; Kavanagh, Turrell et al., 2006;Kim & Kawachi, 2006; Kim et al., 2006; Poortinga,2006b; Subramanian et al., 2002) or different datasource (Browning & Cagney 2002; Kawachi et al.,1999; Subramanian et al., 2001; Wen et al., 2003)

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than the health survey. Our results of individuallevel and work unit level social capital are inagreement with this cross-sectional evidence, andin addition, provide longitudinal evidence of theeffect of changes in social capital on employeehealth.

To date, no general consensus exists about theappropriate level of measurement for social capital.Lochner, Kawachi, and Kennedy (1999) haveargued that processes determining the causes andconsequences of social capital may be quite differentat various levels of aggregation. However, aggre-gated measures of social capital are problematic innumber of ways (Poortinga, 2006a). For example, itis uncertain whether they actually measure socialcapital at the level in question, or whether socialcapital is related to actual second-level character-istics, or to compositional (first level) differences.Mixed findings may be due to several factors,including different conceptualizations or differentsettings, such as workplaces, neighborhoods orareas.

Social capital has been conceptualized as acollective characteristic arising from people’s sharedexperiences and aggregated from the perceptions ofall individuals (Lochner et al., 1999). We were ableto assess an aggregated social capital independentlyof individual perceptions as the work unit levelsocial capital was measured from the perceptions ofsocial capital by the co-workers of the same workunit. Thus, the measure of work unit level socialcapital explicitly described the shared perceptions ofothers in the social environment of the work unit inquestion and was not attributable to self-estimation.Furthermore, as the participants had remained inthe same work unit for the whole study period, thesocial capital was a true characteristic of their workunit, and the change in social capital was notattributable to an individual change in the workunit.

Considering the high variation in the measures ofsocial capital, and a need for research with validatedmeasures, our measure, specially designed to assesssocial capital in work context, has been shown to bea valid measure of social capital at work andindicates whether people feel that they are re-spected, valued and treated as equals at work(Kouvonen et al., 2006). It is based on the inequalityperspective of social capital, a potential mechanismlinking social capital with health. In addition,health-related behaviors as well as social supportand social networks are proposed as pathways

mediating the association between social capitaland health (Kim & Kawachi, 2007; Szreter &Woolcock, 2004). In a recent study Poortinga(2006c) found only limited support that healthbehaviors mediate the association between socialcapital and health. Our results are in line with thesefindings as controlling for health behaviors had noeffect on the association between social capital andhealth. Related to social support at work, there hasbeen a considerable amount of research into theeffects of work social support on health (Stansfeld &Candy, 2006). However, it is important to differ-entiate social capital from social support andnetworks (Harpham et al., 2002). Social capital israther a part of the societal structure than areflection individuals’ social networks and mutualsupport (Subramanian, Lochner, & Kawachi, 2003).

It has been suggested that social capital does notuniformly benefit individuals in the same commu-nity or state (Subramanian et al., 2002). There issome evidence to support this hypothesis in relationto self-rated health. First, some multilevel studieshave reported a cross-level interaction, i.e. themodification of the effects of individual socialcapital on health by the level of social capital ofthe collective (Kim et al., 2006; Poortinga, 2006a;Subramanian et al., 2002). For example, Subrama-nian et al. (2002) found that individuals with lowerlevels of social capital fared worse in the commu-nities of high social capital, and highly trustingindividuals reported worse health when residing inlow-trust communities. However, other studies havefound no evidence of cross-level interaction betweenindividual-level and aggregated-level social capital(Poortinga, 2006b; Subramanian et al., 2001). Ourfindings are in line with the latter studies. We foundno evidence that the two levels of social capitalinteracted with each other (p ¼ 0.33). On thecontrary, the effects of social capital related toindividual and work unit level resulted in similardirections.

Interestingly, however, we found a direct ecolo-gical cross-level effect of working a long time in awork unit, characterized by low levels of socialcapital, on the risk of health impairment (Blakely &Woodward, 2000). Employees in these units had ahigher risk of health impairment at follow-up. Theseresults are in line with previous studies that found ahigher risk of poor health among individuals livingin neighborhoods with the lowest levels of linkingsocial capital (Sundquist & Yang, 2006). In ourstudy, the effect of work unit level social capital on

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health impairment was smaller than that of in-dividual level, as expected, because the variation inecological exposures is often small and may alsovary by level of aggregation (Blakely & Woodward,2000) However, our results provide novel evidenceto the literature about the true contextual effect ofsocial capital on health.

There are some possible explanations for thiscontextual effect. Previous studies in neighborhoodshave shown that neighborhood differences in socialcapital can arise either because of differences inpersonal characteristics and/or because there issomething inherently different about the neighbor-hoods themselves (Subramanian et al., 2003). Thus,observed differences between work units might beconfounded by the characteristics of employees thatconstitute the work units. However, the effectattenuated only slightly and remained significantwhen individual characteristics (other than socialcapital) were added in the model. These results showthat the contextual effects could be accounted foronly in part through compositional factors in thework unit. Second, when contextual characteristicswere adjusted for the effect attenuated to non-significant indicating that work unit social capitaland related effects on health depend on thecharacteristics of work units. It has been suggestedthat social capital may be considerably moreimportant to the disadvantaged (Wakefield &Poland, 2005). We found that the socioeconomicstructure of the work unit, indicated by theproportion of manual workers in the unit, had aspecial role related to the effects of social capital.Only in work units with a high proportion ofmanual workers, work unit social capital signifi-cantly affected the risk of employee health impair-ment and this effect was not accounted for byindividual occupational status. This finding suggeststhat the effects of low social capital might not besimilar in all work units or other groups of differentsocioeconomic structure.

Strengths and limitations

The management of hierarchical data (individualsat first level and work units at second level) allowedus to study the compositional and contextual effectsof social capital on health controlling for individuallevel and work unit level characteristics. Applyingmultilevel statistical methods with employees nestedin work units allowed us to analyze work unitand individual level exposures simultaneously. We

found significant variance in social capital betweenwork units: 22% of the variation in social capitaloccurred at work unit level. The clustering ofindividual social capital within work units indicatesthat work units had influence on social capital, andthat our measurement of social capital at workindeed captured a truly contextual phenomenon.These results strongly supported the use of multi-level modeling in our study.

We had a large number of participants, and wewere able to link them to their work units and studythe real-life characteristics of their social environ-ment at work, such as co-workers’ perceptions ofsocial capital of the unit and socioeconomicstructure in the unit. The validity of our study isfurther strengthened by the fact that the participantsdid not change their work unit during the 4-yearstudy period. Thus, the effect of work unit socialcapital on health was not attributable to a change ofwork unit. Furthermore, in social epidemiology it isimplausible for the effect of an exposure to beinstantaneous (Blakely & Woodward, 2000). Hencewe could avoid misclassification bias related to timelag between an ecological exposure and individuallevel health outcome.

The association between declining individual levelsocial capital at work and health impairment mightbe due to reversed causality, in other wordsattributable to the correlation between the level ofsocial capital at follow-up and the parallel change inhealth at follow-up (Podsakoff, MacKenzie, & Lee,2003). In order to control this bias, we examinedwhether social capital at baseline as such predictedhealth at follow-up. We found that low levels ofbaseline social capital were associated with anincreased risk of health impairment (odds for poorhealth for the lowest vs. the highest quartile of socialcapital, OR 1.46, 95% CI 1.28–1.66), makingreversed causality unlikely as an explanation forour findings.

Another limitation of this study is reliance onself-reported data on health, a method subject toresponse bias (Brick, Kim, Nolin, & Collins, 1996).However, we used a panel design with an initiallyhealthy population at baseline, a strategy allowingthe workers to act as their own controls. All thesenotions make it unlikely that individual traits orresponse styles would explain the results. Anotherlimitation is that there was no control for individualsocial capital outside of work, changes in personalor social life outside workplace, or changes in workshifts. We did not control for race, because our

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cohort consisted of racially homogenous whiteemployees corresponding to Finnish municipalworkers in general. However, future research witha more diverse sample is needed to evaluate thegeneralizability of our findings.

Conclusion

This prospective study suggests that exposure tolow social capital at work poses a risk of healthimpairment. This effect was not accounted for bythe individual perceptions of social capital becausethe adverse effect was also evident in co-worker-assessed social capital. Our study extends theexisting literature with evidence on the contextualeffects of social capital on employee health.

Acknowledgments

This study was supported by the Academy ofFinland (project 105195 and 117604), the FinnishWork Environment Fund (project 103432), theLocal Governments Pensions Institution and theparticipating towns.

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