Behaviors in one person influence behaviors in others in social relations ranging from spouses to siblingsto friends to neighbors. Since the prevalence of obesity has increased from 23% to 31% over the pastdecade, we recently looked for, and found, evidence for the person-to-person spread of obesity in a socialnetwork of 12,630 individuals drawn from the Framingham Heart Study. Here, we propose to build on thiswork by examining whether several health behaviors also evince such spread. Most generally, wehypothesize that the propensity to have a 'healthy diet,' to be physically active, to smoke, and to drink, canspread within social networks via peer effects, and that as one person adopts particular health habits, thoseindividuals to whom s/he is connected will be more likely to adopt similar habits. We also hypothesize thatperson-to-person spread of unhealthy eating behaviors partially explains the network spread of obesity. Wehave 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 orperfecting detailed data on individual eating habits, smoking, drinking, physical activity, and weight for allthese people measured repeatedly from 1971 to the present. Second, we will graphically represent theclustering of individuals with similar health behaviors and the emergence of clusters over time. We willexamine clustering involving both familial (siblings, spouses) and non-familial (friend, neighbor) ties, and wewill account for co-residence. Third, using longitudinal statistical methods, we will evaluate whether healthbehaviors spread from person to person and whether this depends on the nature of the social tie connectingthe ego and the alter or on attributes of the ego and the alter. That is, we will examine whether an increasein an alters' adherence to a healthy diet or initiation or cessation of smoking affects an ego's behaviors. Wewill 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 evaluatewhether spread in the foregoing eating, smoking, drinking, and exercise behaviors helps explain the personto-person spread of obesity. We will 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 workhas implications for the understanding of: cardiovascular risk behaviors and outcomes, social networkexternalities, the determinants of health behaviors, and policy-relevant issues as diverse as socioeconomicdisparities in health or the optimal estimation of the cost-effectiveness of medical care and behavioralinterventions.

Agency
National Institute of Health (NIH)
Institute
National Institute on Aging (NIA)
Type
Research Program Projects (P01)
Project #
1P01AG031093-01
Application #
7393939
Study Section
Special Emphasis Panel (ZAG1-ZIJ-1 (O2))
Project Start
2008-04-15
Project End
2013-03-31
Budget Start
2008-04-15
Budget End
2009-03-31
Support Year
1
Fiscal Year
2008
Total Cost
$282,495
Indirect Cost
Name
Harvard University
Department
Type
DUNS #
047006379
City
Boston
State
MA
Country
United States
Zip Code
02115
Fernández-Gracia, Juan; Onnela, Jukka-Pekka; Barnett, Michael L et al. (2017) Influence of a patient transfer network of US inpatient facilities on the incidence of nosocomial infections. Sci Rep 7:2930
Fu, Feng; Christakis, Nicholas A; Fowler, James H (2017) Dueling biological and social contagions. Sci Rep 7:43634
Glowacki, Luke; Isakov, Alexander; Wrangham, Richard W et al. (2016) Formation of raiding parties for intergroup violence is mediated by social network structure. Proc Natl Acad Sci U S A 113:12114-12119
Kim, David A; Hwong, Alison R; Stafford, Derek et al. (2015) Social network targeting to maximise population behaviour change: a cluster randomised controlled trial. Lancet 386:145-53
O'Malley, A James; Paul, Sudeshna (2015) Using Retrospective Sampling to Estimate Models of Relationship Status in Large Longitudinal Social Networks. Comput Stat Data Anal 82:35-46
Rosenquist, James Niels; Lehrer, Steven F; O'Malley, A James et al. (2015) Cohort of birth modifies the association between FTO genotype and BMI. Proc Natl Acad Sci U S A 112:354-9
Liao, Shu-Yi; Lin, Xihong; Christiani, David C (2015) Occupational exposures and longitudinal lung function decline. Am J Ind Med 58:14-20
O'Malley, A James; Elwert, Felix; Rosenquist, J Niels et al. (2014) Estimating peer effects in longitudinal dyadic data using instrumental variables. Biometrics 70:506-15
Lamont, Elizabeth B; Zaslavsky, Alan M; Subramanian, Subu V et al. (2014) Elderly breast and colorectal cancer patients' clinical course: patient and contextual influences. Med Care 52:809-17
Christakis, Nicholas A; Fowler, James H (2014) Friendship and natural selection. Proc Natl Acad Sci U S A 111 Suppl 3:10796-801

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