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The Spread of Alcohol Consumption Behavior in a Large Social Network

J. Niels Rosenquist, MD, PhD; Joanne Murabito, MD; James H. Fowler, PhD; and Nicholas A. Christakis, MD, PhD
[+] Article and Author Information

From Massachusetts General Hospital, Harvard Medical School, and Boston University School of Medicine, Boston, Massachusetts; University of California, San Diego, San Diego, California; and Harvard University, Cambridge, Massachusetts.


Acknowledgment: The authors thank Laurie Meneades, Rebecca Joyce, Molly Collins, Marian Bellwood, and Karen Mutalik for the expert assistance required to build the data set.

Grant Support: By the National Institutes of Health (grant R01AG2444801) and a Pioneer Award from the Robert Wood Johnson Foundation. The Framingham Heart Study is supported by the National Heart, Lung, and Blood Institute (grant N01HC25195).

Potential Conflicts of Interest: Disclosures can be viewed at www.acponline.org/authors/icmje/ConflictOfInterestForms.do?msNum=M09-1111.

Reproducible Research Statement:Study protocol and data set: Not available. Statistical code: Available from Dr. Fowler (e-mail, jhfowler@ucsd.edu).

Requests for Single Reprints: Nicholas A. Christakis, MD, PhD, Harvard Medical School, 180-A Longwood Avenue, Boston, MA 02115; e-mail, christakis@hcp.med.harvard.edu.

Current Author Addresses: Drs. Rosenquist and Christakis: Harvard Medical School, 180-A Longwood Avenue, Boston, MA 02115.

Dr. Murabito: Boston University School of Medicine, 73 Mount Wayte Avenue, Framingham, MA 01701.

Dr. Fowler: University of California, San Diego, Social Science Building 383, 9500 Gilman Drive, Number 0521, La Jolla, CA 92093-0521.

Author Contributions: Conception and design: J.H. Fowler, N.A. Christakis.

Analysis and interpretation of the data: J.N. Rosenquist, J. Murabito, J.H. Fowler, N.A. Christakis.

Drafting of the article: J.N. Rosenquist, J.H. Fowler, N.A. Christakis.

Critical revision of the article for important intellectual content: J.N. Rosenquist, J. Murabito, J.H. Fowler, N.A. Christakis.

Final approval of the article: J.N. Rosenquist, J.H. Fowler, N.A. Christakis.

Provision of study materials or patients: N.A. Christakis.

Statistical expertise: J.H. Fowler, N.A. Christakis.

Obtaining of funding: J.H. Fowler, N.A. Christakis.

Administrative, technical, or logistic support: J.H. Fowler, N.A. Christakis.

Collection and assembly of data: J. Murabito, J.H. Fowler, N.A. Christakis.


Ann Intern Med. 2010;152(7):426-433. doi:10.7326/0003-4819-152-7-201004060-00007
Text Size: A A A

Background: Alcohol consumption has important health-related consequences and numerous biological and social determinants.

Objective: To explore quantitatively whether alcohol consumption behavior spreads from person to person in a large social network of friends, coworkers, siblings, spouses, and neighbors, followed for 32 years.

Design: Longitudinal network cohort study.

Setting: The Framingham Heart Study.

Participants: 12 067 persons assessed at several time points between 1971 and 2003.

Measurements: Self-reported alcohol consumption (number of drinks per week on average over the past year and number of days drinking within the past week) and social network ties, measured at each time point.

Results: Clusters of drinkers and abstainers were present in the network at all time points, and the clusters extended to 3 degrees of separation. These clusters were not only due to selective formation of social ties among drinkers but also seem to reflect interpersonal influence. Changes in the alcohol consumption behavior of a person's social network had a statistically significant effect on that person's subsequent alcohol consumption behavior. The behaviors of immediate neighbors and coworkers were not significantly associated with a person's drinking behavior, but the behavior of relatives and friends was.

Limitations: A nonclinical measure of alcohol consumption was used. Also, it is unclear whether the effects on long-term health are positive or negative, because alcohol has been shown to be both harmful and protective. Finally, not all network ties were observed.

Conclusion: Network phenomena seem to influence alcohol consumption behavior. This has implications for clinical and public health interventions and further supports group-level interventions to reduce problematic drinking.

Primary Funding Source: National Institutes of Health and the Robert Wood Johnson Foundation. The Framingham Heart Study is supported by the National Heart, Lung, and Blood Institute.

Figures

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Appendix Figure.
Drinking in the Framingham Heart Study social network in 2000.

A sample of the largest component of friends, spouses, and siblings at examination 7 (centered on the year 2000); 1073 individuals are shown. Each node represents 1 person. The graph suggests clustering in abstention and heavy alcohol consumption behavior, both of which are confirmed by statistical models.

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Figure 1.
Relationship of social and geographic distance to heavy drinking and abstaining in connected persons.

We derived effects by comparing the conditional probability of drinking in the observed network with an identical network (with topology preserved) in which the same number of heavy drinkers or abstainers were randomly distributed. “Contact social distance” refers to the closest social distance (or degree of separation) between the contact and principal (for example, a direct friend = 1 and a friend's friend = 2). For geographic distance, we ranked all physical distances between the homes of directly connected principals and contacts (pairs at 1 degree of separation) and created 6 equally sized groups (1 = closest, 6 = farthest). The average distances for these groups are 0 miles (group 1), 0.26 mile (group 2), 1.5 miles (group 3), 3.4 miles (group 4), 9.3 miles (group 5), and 471 miles (group 6).

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Figure 2.
Effect of heavy drinking and abstaining contacts on principals in the Framingham Heart Study social network.

Solid lines are based on bivariate LOESS regression, and dotted lines indicate 95% CIs. Top. Effect of contacts who drink heavily. Bottom. Effect of contacts who abstain.

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Figure 3.
Contact type and drinking in the Framingham Heart Study social network.

Changes in principal alcohol consumption given contact alcohol consumption are shown. Estimates are based on generalized estimating equation logit models of drinking in several subsamples of the Framingham Heart Study social network. The dependent variable in each model is principal drinking status. Independent variables include lagged principal drinking status; contact drinking status; lagged contact drinking status; principal age, sex, and education; and fixed effects for each wave. The Appendix contains full models and equations. To calculate mean effect sizes and Bonferroni-corrected 95% CIs, we simulated first difference in contact contemporaneous drinking (changing from 0 to 1) by using 1000 randomly drawn sets of estimates from the coefficient covariance matrix and assuming all other variables to be held at their means. Top. Effects of heavy drinking. Bottom. Effects of abstention.

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Summary for Patients

Spread of Alcohol Use in a Large Social Network

The summary below is from the full report titled “The Spread of Alcohol Consumption Behavior in a Large Social Network.” It is in the 6 April 2010 issue of Annals of Internal Medicine (volume 152, pages 426-433). The authors are J.N. Rosenquist, J. Murabito, J.H. Fowler, and N.A. Christakis.

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