Social Capital, Social Cohesion and Health
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Transcript of Social Capital, Social Cohesion and Health
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Social Capital, Social Cohesion and Health
Ichiro Kawachi
Professor of Social Epidemiology
Harvard School of Public Health
Sulzberger Colloquium
April 6, 2011
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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.
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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.
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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.
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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
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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
Stu
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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
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Subramanian et al., 2002
Poortinga, 2006a
Poortinga, 2006c
Yip et al., in press
Stu
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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
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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
utho
rs a
nd Y
ear
of P
ublic
atio
n
.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
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Poortinga, 2006a
Poortinga, 2006c
Yip et al., in press
Stu
dy
Au
thor
s an
d Y
ear
of P
ublic
atio
n
.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)
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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).
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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)
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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)
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Fixed effects coefficients for self-rated physical health
*p<0.05*p<0.05
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Fixed effects coefficients for depressive symptoms
*p<0.05
*p<0.05
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Does living in a cohesive community influence health?
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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?
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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…
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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
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Network closure
Johnny
Johnny’s mom
Mrs. Casey (Johnny’s neighbor)
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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
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• Bonding / Bridging• Determinants of community social cohesion• Causal inference
New Directions for Social Capital Research
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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…).
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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.
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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
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“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).
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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.
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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.
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• Bonding / Bridging• Determinants of community social cohesion• Causal inference
New Directions for Social Capital Research
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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
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• Bonding / Bridging• Determinants of community social cohesion• Causal inference
New Directions for Social Capital Research
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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
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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
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Salon Social Programs
←Ping-Pong
Bingo→
Source: Prof. Katsunori Kondo, personal communication
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But Does X really cause Y?
X YParticipation in salons
Good health
β
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Alternative Hypothesis #1: Reverse causation.
(Good health allows you to participate.)
Salon participation Good Health
β
β reverse
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Alternative Hypothesis #2: ConfoundingAssociation may reflect the influence of
omitted variables.
Salon participation Good healthβ
Congeniality, temperament.
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Can we find an instrument?
Participation in salons
Good health
Congeniality, etc.
Z
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Can we find an instrument?
Participation in salons
Good health
Congeniality, etc.
Distance to nearest salon
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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
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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 )
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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.
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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
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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 2-year follow-up period, adjusting for baseline health.
Professor Katsunori Kondo,Nihon Fukushi University