Spencer Moore, Stephanie Child, Yun-Hsuan, and Jennifer Mandelbaum

Spencer Moore[1], Stephanie Child[2], Yun-Hsuan[3], and Jennifer Mandelbaum[4]

 These authors describe the history of social capital definitions over the past 20 years. These began with the cohesion approach, also called the contextual, as developed by Putnam (1995). He described the social capital context of social groups or whole communities by its stocks of trust, norms, and social participation. In the early 2000s the network approach appeared, the focus of this chapter, which developed methods of measuring social resources and networks, focusing on the connections of individual actors and the nature of these ties. The main research designs feature the individual, the “ego”, the whole network, and the means to identify further connections, the “snowball” method.

How does the network work to influence health related behaviors? These social groups provide social influences, support, and access to resources provided by significant others regarding healthy behaviors. Social support provided by significant others are measured by name generators, position generators, and resource generators. Name generators identify the individuals in the network and their contacts, or “alters” and the nature of these ties. Contacts with people of status in their communities are developed by position generators, while resource generators are described by the subject’s choices from a list of accesses to specific resources and the strength of these ties.

A review of empirical studies provides the evidence of the network social capital effects on health-related behaviors. Larger networks are associated with longer durations of people’s maintenance of physical activity. Networks consisting mainly of family members have the lowest odds of physical activity engagement (Litwin, 2003). Networks of people who exercise are more advantageous to older adults (Lereux et al, 2003). Similarly, studies of problem drinking, assessed where college roommates are picked by assignment, indicate that rooming with a heavy drinker is more likely to encourage binging and drinking more frequently (Guo et al, 2015). Local groups with more diverse people are positively associated with drinking (Dorsey et al, 1999). Among men, larger groups of heavy drinkers have more “drinking buddies”. Smoking is more influenced by family members than the influence of co-workers and neighbors (Christakis and Fowler, 2008). Relapse of efforts to quit smoking are less likely with people in social groups with higher social capital (Moore et al, 2014). Longitudinal study showed that risks of obesity is increased if their friends, siblings or spouse becomes obese (Christakis and Fowler, 2007). In contrast, clinical mental health conditions, such as depression and anxiety, are not influenced by network social capital, but are benefited by cohesion social capital (Whitley and McKenzie, 2005).

Conclusions:

These findings from network theory, where they correspond in the issues and ideas, provide a unity of social capital research studies despite contrasting methods. Network approaches clearly play an essential role in social capital research. Complete references can be found in the chapter (Ch 15 in Elgar Companion to Social Capital and Health).

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[1] Spencer Moore is Associate Professor in the Department of Health Promotion, Education, and Behavior, Arnold School of Public Health University of South Carolina, USA.

[2] Stephanie Child is a postdoctoral research fellow with the Berkeley Population Center, University of California, Berkeley, USA.

[3] Yun-Hsuan Wu, is Postdoctoral Fellow in the McGill Centre for Convergence of Health and Innovation (MCCHE) at McGill University, Canada.

[4] Jennifer Mandelbaum is a PhD student in Health Promotion, Education, and Behavior at the University of South Carolina, USA.

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