social capital, social cohesion and health

Social Capital, Social Cohesion and Health

Ichiro Kawachi

Professor of Social Epidemiology

Harvard School of Public Health

Sulzberger Colloquium

April 6, 2011

Conceptual approaches to defining “social capital”

Level of Analysis Individual Group

SC as Cohesion

SC as Networks

Source: Kawachi, “Social Capital and Health”, In: Handbook of Medical Sociology, 6th edition (2010), chapter 2.

Conceptual approaches to defining “social capital”

Level of Analysis Individual Group

SC as Cohesion • Perceptions of trust

• Civic participation

• Volunteering.

• Survey responses aggregated to the group level.

SC as Networks

Source: Kawachi, “Social Capital and Health”, In: Handbook of Medical Sociology, 6th edition (2010), chapter 2.

Conceptual approaches to defining “social capital”

Level of Analysis Individual Group

SC as Cohesion • Perceptions of trust

• Civic participation

• Volunteering.

• Survey responses aggregated to the group level.

SC as Networks • Position Generator

• Resource Generator

• Whole social network analysis

Source: Kawachi, “Social Capital and Health”, In: Handbook of Medical Sociology, 6th edition (2010), chapter 2.

State of Empirical Evidence

• Most studies cross-sectional.

• Majority of studies have focused on individual-level social capital (trust perceptions, associational membership).

• Most studies used self-rated health as endpoint.

• Demonstration of contextual effects remain elusive.

Springer, 2008

Hyppaa & Maki (men), 2001

Hyppaa & Maki (women), 2001

Subramanian et al., 2002

Pollack & Knesebeck, 2004

Veenstra, 2005a

Kim et al., 2006a

Kim et al., 2006b

Poortinga, 2006a

Poortinga, 2006b

Poortinga, 2006c

Poortinga, 2006d

Yip et al., in press

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.3 .4 .5 .6 .7 .8 .9 11 1.5 2Odds Ratio and 95% Confidence Interval

Figure 1: Studies of Individual-Level Trust and Fair/Poor Self-Rated Health (Dichotomous)

Source: Kim, Subramanian & Kawachi, 2008. Chapter 8

Systematic Review of Studies, 1996-November 1, 2006

Subramanian et al., 2002

Poortinga, 2006a

Poortinga, 2006c

Yip et al., in press

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.3 .4 .5 .6 .7 .8 .9 11 1.5 2Odds Ratio and 95% Confidence Interval

With Adjustment for Individual-Level Social CapitalFigure 2A: Studies of Area-Level Trust and Fair/Poor Self-Rated Health (Dichotomous)

Source: Kim, Subramanian & Kawachi, 2008. Chapter 8

Hyppaa et al. (men), 2001

Hyppaa et al. (women), 2001

Hyppaa et al., 2003

Lindstrom, 2004

Pollack & Kneseback, 2004

Veenstra, 2005a

Kim et al., 2006b

Poortinga, 2006a

Poortinga, 2006b

Poortinga, 2006c

Poortinga, 2006d

Yip et al., in press

Stu

dy A

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nd Y

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of P

ublic

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.3 .4 .5 .6 .7 .8 .9 11 1.5 2Odds Ratio and 95% Confidence Interval

Figure 3: Studies of Individual-Level Associational Memberships and Fair/Poor Self-Rated Health (Dichotomous)

Source: Kim, Subramanian & Kawachi, 2008. Chapter 8

Poortinga, 2006a

Poortinga, 2006c

Yip et al., in press

Stu

dy

Au

thor

s an

d Y

ear

of P

ublic

atio

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.3 .4 .5 .6 .7 .8.911 1.5 2Odds Ratio and 95% Confidence Interval

With Adjustment for Individual-Level Social CapitalFigure 4A: Studies of Area-Level Associational Memberships and Fair/Poor Self-Rated Health (Dichotomous)

Problems in Causal Inference

Common method variance

Omitted variable bias (e.g. early childhood environment resulting in poor attachment and poor health).

Reverse causation (e.g. people participate because they are healthy).

What can twin studies accomplish?

• Control for inherited characteristics (e.g. temperament, personality, ability).

• Control for early rearing environment (e.g. poor attachment → poor social relations & poor health in adulthood)

The National Survey of Midlife Development in the US (MIDUS) Twin Study,1995-1996

Twin screening for ~50,000 national representative sample

Final study sample (N=944 pairs)

14.8% presence of twin

60% gave permission to access twin

26% Completed interview (N=998 pairs)

Exclude unknown zygosity and separated before 14 (N=54 pairs)

Fixed effects coefficients for self-rated physical health

*p<0.05*p<0.05

Fixed effects coefficients for depressive symptoms

*p<0.05

*p<0.05

Does living in a cohesive community influence health?

Indicators of community social cohesion

Presence of active community organizations- neighborhood watch group.

Informal socializing.- do you have block parties?

Neighbors constantly helping each other.- will they pick up your kids from the bus stop?

Trust between neighbors.- do you leave your door unlocked when you go out?

Mechanisms linking social cohesion to health outcomes

Collective action & collective efficacy

e.g. mobilizing to protest the closure of emergency services; passage of local smoke-free ordnances…

Informal social control

the role of community adults (as opposed to the police) in intervening to stop smoking, drinking, drug use by children.

Mechanisms linking social cohesion to health outcomes

Network closure

Johnny

Johnny’s mom

Mrs. Casey (Johnny’s neighbor)

Exchange of favors / diffusion of information.

More cohesive communities

= more network closure (all your

friends know each other).

= less likelihood of free-

riding (i.e. receiving

favors without reciprocating)

because of risk to one’s

reputation.

Mechanisms linking social cohesion to health outcomes

• Bonding / Bridging• Determinants of community social cohesion• Causal inference

New Directions for Social Capital Research

Bonding vs. Bridging Social Capital

Bonding social capital

– social connections between people who are similar to each other in terms of status (race, social class, gender…).

Bonding vs. Bridging Social Capital

Bonding social capital

– social connections between people who are similar to each other in terms of status (race, social class, etc).

e.g. the Ku Klux Klan.

Bonding vs. Bridging Social Capital

Bridging social capital

– social connections that bridge different SES and race/ethnic groups.

e.g. integrated Hindu/Muslim associations in India.

Yale University Press, 2002

“Do bonding and bridging social capital have differential effects on self-rated health? A community based study in Japan.”

T. Iwase, E. Suzuki, T. Fujiwara, S. Takao, Doi H, Kawachi I. 　JECH, December 16 (2010).

Community sample of 2,260 Okayama City residents, 20-80 years old.

Inquired about participation in a variety of civic associations (PTA, sports clubs, alumni associations, political campaign clubs, citizen’s groups, and community associations).

Distinguished bonding vs. bridging social capital (diversity by occupation, age group, gender).

Multivariable-adjusted* odds ratios of poor self-rated health.

Type of social capital OR (95% CI)

Bonding capital

None Low Middle High

1.000.82 (0.59-1.13)0.81 (0.49-1.34)0.68 (0.32-1.44)

*adjusted for sex, age, living arrangement, education, smoking, overweight, and other type of social capital.

Type of social capital OR (95% CI)

Bonding capital

None Low Middle High

1.000.82 (0.59-1.13)0.81 (0.49-1.34)0.68 (0.32-1.44)

Bridging capital

None Low Middle High

1.000.72 (0.53-0.98)0.61 (0.41-0.91)0.33 (0.19-0.58)

*adjusted for sex, age, living arrangement, education, smoking, overweight, and other type of social capital.

Multivariable-adjusted* odds ratios of poor self-rated health.

• Bonding / Bridging• Determinants of community social cohesion• Causal inference

New Directions for Social Capital Research

Methods(slide courtesy of Dr. Tomoya Hanibuchi)

• Using　GIS　and　topographical　maps

• 5　cross　sections:　　　　t1　(pre-1890)

t2　(1890-1920)　

　　　t3　(1920-1960)

t4　(1960-1980)　

　　 t5　(post-1980)

t1t2

t3t4

t5

Settlements

Individual　samples

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OR (95% CI) by periods (t1 ~ t5) for SC indicators,estimated by logistic regression models

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Courtesy　of　Dr.　Tomoya　Hanibuchi

• Bonding / Bridging• Determinants of community social cohesion• Causal inference

New Directions for Social Capital Research

study area

0 5 102.5km

N

Aichi PrefectureTokai Obu

Chita

Agui

Taketoyo

Mihama

Minamichita

Higashiura

Chita Peninsula

Nagoya

←Taketoyo 　　　　　town

Taketoyo town population 42,000 45 min from Nagoya

Taketoyo Town Intervention

In 2007, municipal officials launched campaign to promote healthy aging among citizens.

Intervention: Opening of community centers for seniors, called “salons”.

Managed by volunteers.

Some of the town residents were also participants of an ongoing cohort study (Aichi Gerontological Evaluation Study, AGES).

Source: Prof. Katsunori Kondo, personal communication

Salon Social Programs

←Ping-Pong

Bingo→

Source: Prof. Katsunori Kondo, personal communication

But Does X really cause Y?

X YParticipation in salons

Good health

β

Alternative Hypothesis #1: Reverse causation.

(Good health allows you to participate.)

Salon participation Good Health

β

β reverse

Alternative Hypothesis #2: ConfoundingAssociation may reflect the influence of

omitted variables.

Salon participation Good healthβ

Congeniality, temperament.

Can we find an instrument?

Participation in salons

Good health

Congeniality, etc.

Z

Can we find an instrument?

Participation in salons

Good health

Congeniality, etc.

Distance to nearest salon

3 sites in 2007 & participants

● 　 participants

Circle 　 shows 　500m

□ 　 site

2007 　 3 sites2008 　 2 sites2009 　 2sitesBy 2012: total 10 sites

most participants come from neighborhood

Source: Prof. Katsunori Kondo, personal communication

Distance from salons as an instrumental variable

Distance from salon

% of participants per older persons

living in the distance bracket

N → （ 414 ）　　（ 860 ）　　（ 607 ）　　（ 477 ）　（ 264 ）　　（ 206 ）　　（ 281 ）　　（ 209 ）　（ 630 ）

2 Stage Least Squares (2SLS)

edictorsPrOther X̂ k

edictorsPrOther X̂Y k

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Participation in the salons & Trust

• Distance to the salons showed significant linkage to participation to the salons.

• The estimated participation in the salons had a marginally significant (10%) effect on trust in 2008 independent of age, sex and trust in 2006.

P-values are in parentheses.

(0.061) (0.598) (0.568) (0.000) (0.663)

ionparticipat0.39age06.00240 male.0260 Ztrust06.4800.15 Ztrust08

(0.000) (0.000)

distance0.690.68onarticipatip̂

iiiiii

iii

u

v

Test for regressor endogeneityIn Likelihood Ratio test, H0:ρ(the error correlation)=0 was not rejected (p=0.25), ”participation” is not necessarily an endogenous variable.

46

P-values are in parentheses.

(0.022) (0.000) (0.160) (0.000) (0.000)

ionparticipat0.43age06.0190 male0.060 Zsrh06.5001.45 Zsrh08

(0.000) (0.000)

distance0.690.68onarticipatip̂

iiiiii

iii

u

v

• Distance to the salons showed significant linkage to participation in the salons.

• The estimated participation in the salons had a significant (5%) effect on SRH in 2008 independent of age, sex and SRH in 2006.

Test for regressor endogeneityIn Likelihood Ratio test, H0:ρ(the error correlation)=0 was not rejected (p=0.33), ”participation” is not necessarily an endogenous variable.

Participation in the salons & SRH

Findings

• ↓distance from salon = ↑participation.

• ↑participation (instrumented) = ↑trust of others over 2-year follow-up period, adjusting for baseline trust.

• ↑participation (instrumented) = ↑self-rated health over 2-year follow-up period, adjusting for baseline health.

Professor Katsunori Kondo,Nihon Fukushi University