This study investigated the reciprocal relationships between social network characteristics, social support, and mental health among older adults in the United States. The study found reciprocal associations between social support and depressive symptoms, as well as between social support and certain measures of social network structure. While social support was protective of depression, depression could undermine received support over time. The strongest link between social networks and depression was indirect, through levels of social support. Future research should focus on social support as an important pathway through which social networks impact mental health.

1. RECIPROCAL RELATIONSHIP BETWEEN
SOCIAL NETWORK CHARACTERISTICS
AND MENTAL HEALTH AMONG OLDER
ADULTS IN THE UNITED STATES:
DIFFERENTIATING BETWEEN NETWORK
STRUCTURE AND NETWORK FUNCTION
BONNIE BUI
POSTDOC FELLOW, TULANE UNIVERSITY
CENTER FOR STUDIES OF DISPLACED POPULATIONS
DNAC 2019 SOCIAL NETWORKS & HEALTH WORKSHOP

2. INTRODUCTION TO THE PROBLEM
• Depression among older adults is often related to other physical health
outcomes.
• Because of increased risk for chronic conditions and functional limitations
among older adults, older adults are at increased risk for chronic
depression.
• The maintenance of social relationships is an important component of
older adult mental health.

3. INTRODUCTION TO THE PROBLEM
• Prior research have found:
• The characteristics of a network (e.g., number of ties and how supportive those ties
are) have impacts on mental health, both perceived and actual.
• Social support can buffer individuals from impacts of stressful life events (stress buffer
hypothesis).
• However, poor mental health may make maintenance of an individual’s
network difficult, compromising the ability to derive any potential benefits
from social support.

4. LITERATURE OVERVIEW
• Social Relationships and Health are linked (Berkman et al. 2000; Umberson and Montez
2010)
• Increased risk of mortality for persons with low quantity, and sometimes low quality, of social
relationships (House, Landis, and Umberson 1988)
• Socially isolated individuals are less able to buffer the impact of health stressors, putting them
at greater risk for negative health outcomes (House et al. 1988).
• Some of the ways social relationships can potentially influence health are through the
following:
• Social support (Thoits 1995)
• Social influence (Friedkin 2001)
• Social engagement (Glass et al. 2006)
• Person-to-person contact (Laumann et al. 1989)
• Access to material resources (Granovetter 1973)

5. RATIONALE FOR THE CURRENT STUDY
• In the literature, there is more attention paid to how changes in social
networks and support affect health.
• Less attention to how changes in baseline health impact changes in social
networks.
• Findings in the literature are inconsistent, which is largely due to different
ways of operationalizing networks, support, and health.
• Much of the research in the literature also sometimes conflate network
structure with social support.

6. RESEARCH GOALS
• The purpose of this research is to investigate whether there is reciprocal
(bidirectional) associations between personal/local network characteristics
and health outcomes among older adults, using various measures for
different dimensions on egocentric network structure to find which specific
network characteristics matter, and in what way.
• My focus is on conceptually distinguishing network structure and social
support by using derived egocentric network measures from roster data to
represent network structure.

7. DISTINCTION BETWEEN NUMBER AND
QUALITY OF TIES
• Social support is not an inherent part of social ties. Social ties can also be
sources of social stress that manifests itself in worsening health (Walen
and Lachman 2000).
• Social integration may be a necessary but not sufficient condition for good
health. Beyond merely being socially integrated, having supportive ties is
important for health.
• A distinction needs to be made between social integration and having supportive ties
(Berkman and Glass 2000).

8. SOCIAL NETWORKS AND SUPPORT INFLUENCES MENTAL
HEALTH.

9. HEALTH ALSO INFLUENCES INDIVIDUALS’ ABILITY TO FORM
OR MAINTAIN NETWORKS.

10. RESEARCH QUESTIONS
• Does local network structure affect depressive symptoms for older adults?
• Does social support affect depressive symptoms for older adults?
• Do older adults’ depressive symptoms affect local network structure?
• Do older adults’ depressive symptoms affect social support?

11. DATA
• National Social Life, Health, and Aging Project (NSHAP)
• Survey uses a national area probability sample of adults born between
1920 and 1947, or ages 57 to 85 at the time of the Wave 1.
• Two waves:
• Wave 1, 3,005 interviews, 2005-2006
• Wave 2, 3,377 interviews, 2010-2011
• I only use data from adults who were re-interviewed at Wave 2 (N=2.261).

12. APPROPRIATENESS OF DATA
• Dataset is appropriate because two time points allow analysis of change in
5 years, although it is unknown whether this lag is too long when looking at
the impacts of networks on health.
• Includes detailed social network data

13. SOCIAL NETWORK ROSTER DATA
• Social Network Roster
• Respondents were asked to identify some of the people they interact with on a regular
basis and are asked the following:
• What their relationship is to each person
• Whether each person named resides in the same household
• Their gender and whether older or younger than the respondent
• Frequency of contact
• Closeness of the relationship
• Questions on instrumental support, emotional openness, and level of demands person
made on respondent
• How frequently each person named talked to others who were named

14. MEASURES
• Mental Health
• Depressive Symptoms (11-item CES-D scale)
• Network Structure
• Network size (sum of alters)
• Number living with ego
• Proportion female
• Number of close ties
• Density (ratio of actual ties to total possible ties)
• Frequency of contact with alters (summed across all alters)

15. MEASURES
• Social Support
• Perceived social support from family and friends (4-item scale)
• Demographic and Control Variables
• Age
• Indicator for female
• Indicator for white
• Indicator for college
• Cohabitation Status

16. RESEARCH METHOD
• Longitudinal analyses: conditional change method(refer to Paul Allison)
• Used to examine change in dependent variables between waves.
• Examine the relationship between an independent variable and a dependent variable
at time 2 while controlling for the effects of that dependent variable at time 1 by
including a lagged dependent variable in the model.
• Allows us to account for baseline differences between respondents.
• OLS regression to examine whether depressive symptoms, support, and
network characteristics predict changes for future depressive symptoms,
support, and networks, five years from the baseline survey.

17. IMPUTATION AND WEIGHTING
• Imputation:
• Multiple imputation with chained equations (MICE) to address missing data
• Weighting:
• “svyset” commands in Stata/SE 15.1 to adjust for nonresponse and correct for
sampling design

18. SAMPLE DESCRIPTIVES
Wave 1 Wave 2
Variables % or Mean SD Range % or Mean SD Range
Health Outcome
Depressive Symptoms 4.679 (.103)0 to 20 4.702 (.126)0 to 21
Network Structure
Network size 4.544 (.060)2 to 14 4.665 (.054)2 to 14
Number living with ego 1.038 (.028)0 to 11 0.978 (.027)0 to 9
Proportion female 0.608 (.008)0 to 1 0.607 (.006)0 to 1
Number of close ties 3.455 (.053)0 to 7 3.421 (.048)0 to 7
Density 0.835 (.008)0 to 1 0.827 (.008)0 to 1
Frequency of contact with alters (contact-days per year) 820.578 (9.455)0 to 2190 817.795 (11.001)0 to 2555
Social Support
Perceived support 5.268 (.054)0 to 8 5.227 (.057)0 to 8
Demographic Variables (only W1)
Age 67.306 (.230)57 to 85
Female 52.1
White 80.6
College or higher 26.7
Cohabiting 66.9

20. LOCAL NETWORK & SUPPORT  CES-D
• Social support positively associated with later depressive symptoms.
• Density negatively associated with later depressive symptoms.

22. LOCAL NETWORK & CES-D  SUPPORT
• Close ties and frequency of tie activation are positively associated with
social support.
• Depressive symptoms at time 1 negatively associated with perceived
social support 5 years later.

24. CES-D & SUPPORT  LOCAL NETWORK
• Support at time 1 positively associated with the network size, number of
close ties, and contact with alters at time 2.

25. SUMMARY OF FINDINGS
• Reciprocal associations between social support and CES-D, as expected.
• Support is protective of depression, but depression can undermine support.
• Reciprocal associations between social support and select local network
measures (number of close ties and frequency of contact with alters).
• No reciprocal associations between CES-D and local network measures.
• Influence of local network on CES-D is largely indirect through social support.

26. • Of local network measures, only density associated with later depressive
symptoms.
• Association is positive, which is counter to the expectation that more connected
networks would be protective of mental health because of higher levels of social
support in denser networks.
• Possible explanation: Depressed individuals have fewer friends, resulting in smaller
and denser networks.
• Strongest link between local network and CES-D is social support.
• Future research should focus on social support as an important pathway in
which personal networks can impact mental health.

27. REFERENCES
• Berkman, Lisa F. and Thomas Glass. 2000. “Social Integration, Social Networks, Social Support, and Health.” In Social Epidemiology. New York:
Oxford Univ. Press.
• Berkman, Lisa F., Thomas Glass, Ian Brissette, and Teresa E. Seeman. 2000. “From Social Integration to Health: Durkheim in the New Milennium.”
Social Science & Medicine 51(6):843-857.
• Friedkin, Noah E. 2001. “Norm Formation in Social Influence Networks.” Social Networks 23(3):167-189.
• Glass, Thomas A., Carlos F. Mendes De Leon, Shari S. Bassuk and Lisa F. Berkman. 2006. “Social Engagement and Depressive Symptoms in Late
Life: Longitudinal Findings.” Journal of Aging and Health 18(4):604-628.
• Granovetter, Mark S. 1973. “The Strength of Weak Ties.” American Journal of Sociology 78(6):1360-1380.
• House, James S., Karl R. Landis and Debra J. Umberson. 1988. “Social Relationships and Health.” Science 241(4865):540-545.
• Laumann, Edward O., John H. Gagnon, Stuart Michaels, Robert T. Michael and James S. Coleman. 1989. “Monitoring the AIDS Epidemic in the
United States: A Network Approach.” Science 244(4909):1186-1189.
• Thoits, Peggy A. 1995. “Stress, Coping, and Social Support Processes: Where Are We? What Next?” Journal of Health & Social Behavior
Special(1995):53-79.
• Umberson, Debra, and Jennifer Karas Montez. 2010. “Social Relationships and Health: A Flashpoint for Health Policy.” Journal of Health and Social
Behavior 51(S):S54-S66.
• Walen, Heather R. and Margie E. Lachman. 2000. “Social Support and Strain from Partner, Family, and Friends: Costs and Benefits for Men and
Women in Adulthood. Journal of Social and Personal Relationships 17:5-30.

28. Thank you! Any additional comments and suggestions,
please send to bbui@tulane.edu