This work builds on previous research of ours on the spread of health phenomena within the Framingham Heart Study (FHS) cohorts. Since the prevalence of obesity has increased from 23% to 31% over the past decade, we recently looked for, and found, evidence for the person-to-person spread of obesity in a social network of 12,630 individuals drawn from the FHS. Here, we build on this work by examining whether several health behaviors also evince such spread. Most generally, we hypothesize that the propensity to have a “healthy diet,” to be physically active, to smoke, and to drink, can spread within social networks via peer effects, and that as one person adopts particular health habits, those individuals to whom s/he is connected will be more likely to adopt similar habits. We also hypothesize that person-to-person spread of unhealthy eating behaviors partially explains the network spread of obesity. We have four specific aims. First, we will embellish a longitudinal dataset describing 5,124 individuals (“egos”) and a social network of 12,630 people in which they are embedded (their possible “alters”), by obtaining or perfecting detailed data on individual eating habits, smoking, drinking, physical activity, and weight for all these people measured repeatedly from 1971 to 2007.  Second, we will graphically represent the clustering of individuals with similar health behaviors and the emergence of clusters over time, involving both familial and non-familial (e.g., friend, neighbor) ties. Third, using longitudinal statistical methods, we will evaluate whether health behaviors spread from person to person and whether this depends on the nature of the social tie connecting the ego and the alter or on attributes of the ego and the alter. That is, we will examine whether an increase in an alter’s adherence to a healthy diet or initiation or cessation of smoking affects an ego’s like behaviors.  And we will consider whether transmission of eating behaviors is more effective among people with certain attributes (e.g., women, high education) or certain relationships (e.g., friends, neighbors). Fourth, we will evaluate whether spread in the foregoing eating, smoking, drinking, and exercise behaviors helps explain the person-to-person spread of obesity. We examine these network effects in the context of cardiovascular disease, which is responsible for 40% of deaths in the U.S. and incurs costs of over $350 billion annually. Our work has implications for the understanding of: cardiovascular risk behaviors and outcomes, social network externalities, the determinants of health behaviors, and policy-relevant issues as diverse as socioeconomic disparities in health and the optimal estimation of the cost-effectiveness of medical care and behavioral interventions.

Papers published so far based on this work include:

N.A. Christakis, “Social Networks and Collateral Health Effects Have Been Ignored in Medical Care and Clinical Trials, But Need to Be Studied,” British Medical Journal 329: 184-185 (July 2004).

N.A. Christakis and J. Fowler, “The Spread of Obesity in a Large Social Network Over 32 Years,” The New England Journal of Medicine (July 2007).

N.A. Christakis and J. Fowler, “The Collective Dynamics of Smoking in a Large Social Network,” The New England Journal of Medicine, 358(21): 2249-2258 (May 2008).

Rosenquist JN, Fowler JH, Christakis NA. "The spread of depression in a large social network." Molecular Psychiatry, (16 March 2010) | doi:10.1038/mp.2010.13 

Rosenquist JN, Fowler JH, Murabito J, Christakis NA.  "The spread of alcohol consumption behavior in a large social network." Annals of Internal Medicine, 2010: 152(7), 426-433.