Transcript Slide 1

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
SC as Cohesion
• Perceptions of trust
• Civic participation
Group
• Survey responses
aggregated to the group
level.
• Volunteering.
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
SC as Cohesion
• Perceptions of trust
Group
• Survey responses
aggregated to the group level.
• Civic participation
• Volunteering.
SC as Networks
• Position Generator
• Whole social network
analysis
• Resource Generator
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
Figure 1: Studies of Individual-Level Trust and Fair/Poor Self-Rated Health (Dichotomous)
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
.3
.4
.5
.6
.7
.8
.9
1
Odds Ratio and 95% Confidence Interval
Systematic Review of Studies, 1996-November 1, 2006
Source: Kim, Subramanian & Kawachi, 2008. Chapter 8
1.5
2
Figure 2A: Studies of Area-Level Trust and Fair/Poor Self-Rated Health (Dichotomous)
With Adjustment for Individual-Level Social Capital
Subramanian et al., 2002
Poortinga, 2006a
Poortinga, 2006c
Yip et al., in press
.3
.4
.5
.6
.7
.8
.9
1
Odds Ratio and 95% Confidence Interval
Source: Kim, Subramanian & Kawachi, 2008. Chapter 8
1.5
2
Figure 3: Studies of Individual-Level Associational Memberships and Fair/Poor Self-Rated Health (Dichotomous)
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
.3
.4
.5
.6
.7
.8
.9
1
Odds Ratio and 95% Confidence Interval
Source: Kim, Subramanian & Kawachi, 2008. Chapter 8
1.5
2
Figure 4A: Studies of Area-Level Associational Memberships and Fair/Poor Self-Rated Health (Dichotomous)
With Adjustment for Individual-Level Social Capital
Poortinga, 2006a
Poortinga, 2006c
Yip et al., in press
.3
.4 .5 .6 .7 .8.91
1
1.5
2
Odds Ratio and 95% Confidence Interval
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
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)
Final study sample
(N=944 pairs)
Fixed effects coefficients for self-rated physical health
MZ
DZ
0.25
0.2
0.15
0.1
0.05
0
-0.05
-0.1
-0.15
Social trust
*p<0.05
*p<0.05
Sense of
belonging
Volunteer
activity
Community
participation
Fixed effects coefficients for depressive symptoms
MZ
DZ
0.15
0.1
Social trust
0.05
Sense of
belonging
Volunteer activity
0
-0.05
-0.1
-0.15
-0.2
-0.25
-0.3
*p<0.05
*p<0.05
Community
participation
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…
Mechanisms
linking social cohesion to health outcomes

Informal social control
the role of community
adults (as opposed to the
police) in intervening to
stop smoking, drinking,
drug use by children.
Network closure
Johnny’s mom
Mrs. Casey
(Johnny’s
neighbor)
Johnny
Mechanisms
linking social cohesion to health outcomes

Exchange of favors / diffusion of information.

More cohesive communities
= more network closure (all your
friends know each other).
= less likelihood of freeriding (i.e. receiving
favors without reciprocating)
because of risk to one’s
reputation.
New Directions for
Social Capital Research
• Bonding / Bridging
• Determinants of community social cohesion
• Causal inference
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
1.00
0.82 (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.
Multivariable-adjusted* odds ratios of
poor self-rated health.
Type of social capital
OR (95% CI)
Bonding capital
None
Low
Middle
High
1.00
0.82 (0.59-1.13)
0.81 (0.49-1.34)
0.68 (0.32-1.44)
Bridging capital
None
Low
Middle
High
1.00
0.72 (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.
New Directions for
Social Capital Research
• Bonding / Bridging
• Determinants of community social cohesion
• Causal inference
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)
t3
t2
t1
Settlements
t4
t5
Individual samples
31
OR (95% CI) by periods (t1 ~ t5) for SC indicators,
estimated by logistic regression models
32
Courtesy of Dr. Tomoya Hanibuchi
New Directions for
Social Capital Research
• Bonding / Bridging
• Determinants of community social cohesion
• Causal inference
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?
β
X
Participation in
salons
Y
Good health
Alternative Hypothesis #1:
Reverse causation.
(Good health allows you to participate.)
Salon
participation
β
β reverse
Good Health
Alternative Hypothesis #2: Confounding
Association may reflect the influence of
omitted variables.
Salon participation
β
Congeniality,
temperament.
Good health
Can we find an instrument?
Z
Participation in
salons
Good health
Congeniality,
etc.
Can we find an instrument?
Distance to nearest
salon
Participation in
salons
Good health
Congeniality,
etc.
3 sites in 2007 & participants
□ site
Circle shows
500m
most participants
come from
neighborhood
● participants
2007 3 sites
2008 2 sites
2009 2sites
By 2012: total 10 sites
Source: Prof. Katsunori Kondo, personal communication
% of participants per older persons
living in the distance bracket
Distance from salons as an instrumental
variable
25
20
15
10
5
0
N → （414）
（860）
（607）
（477） （264）
（206）
Distance from salon
（281）
（209） （630）
2 Stage Least Squares (2SLS)
ˆ        Other Pr edictors
X


k
ˆ   Other Pr edictors  
Y     X
k
Participation in the salons & Trust
P-values are in parentheses.
pˆ articipati on i   0.68  0.69  distance
(0.000)
Ztrust08
i
 vi
(0.000)
 0.15  0 .48  Ztrust06
(0.663)
i
(0.000)
i
 0 .026  male
(0.568)
i
 0 .0024  age06
(0.598)
i
 0.39  participat ion i  u i
(0.061)
• 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.
Test for regressor endogeneity
In Likelihood Ratio test, H0:ρ(the error correlation)=0 was not rejected (p=0.25),
”participation” is not necessarily an endogenous variable.
45
Participation in the salons & SRH
P-values are in parentheses.
pˆ articipati on i   0.68  0.69  distance
(0.000)
Zsrh08
i
(0.000)
 vi
(0.000)
 1.45  0 .50  Zsrh06
(0.000)
i
i
0.060  male
(0.160)
i
0 .019  age06
(0.000)
i
 0.43  participat ion i  u i
(0.022)
• 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 endogeneity
In Likelihood Ratio test, H0:ρ(the error correlation)=0 was not rejected (p=0.33),
”participation” is not necessarily an endogenous variable.
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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 2year follow-up period, adjusting for baseline health.
Professor Katsunori Kondo,
Nihon Fukushi University