The spread of alcohol consumption behavior in a large social network.
- Authors
- Rosenquist, J Niels; Murabito, Joanne; Fowler, James H; Christakis, Nicholas A
- Year
- 2010
- Journal
- Annals of internal medicine
- PMID
- 20368648
- DOI
- 10.7326/0003-4819-152-7-201004060-00007
- PMCID
- PMC3343772
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.
Drinking in the Framingham Social Network in 2000This graph shows a sample the largest component of friends, spouses, and siblings at exam 7 (centered on the year 2000). There are 1,073 individuals shown. Each node represents a subject and its shape denotes gender (circles are male, squares are female). Lines between nodes indicate relationship (grey for siblings, green for friends and spouses). Node color denotes alcohol consumption behavior: red nodes indicate abstention, blue nodes indicate heavy drinking (more than one drink per day for women and more than two drinks per day for men), and yellow nodes indicate moderate intake between these two extremes. The graph suggests clustering in abstention and heavy alcohol consumption behavior, both of which are confirmed by statistical models discussed in the main text and presented in the supplement.
LLM interpretation
This is a network graph representing the social connections of 1,073 individuals, where nodes denote subjects and edges represent relationships (grey for siblings, green for friends/spouses). Nodes are categorized by gender (circles for male, squares for female) and alcohol consumption behavior (red for abstention, blue for heavy drinking, and yellow for moderate intake). The visualization shows a clustering pattern where nodes of the same color, particularly red and blue, tend to group together.
Relationship of Social and Geographic Distance to Heavy Drinking and Abstaining in Connected PersonsTop panels show the effect of social and geographic distance from heavy-drinking contacts on the probability that a principal is a heavy drinker in the Framingham Heart Study Social Network. Heavy drinking is defined in this case as having more than one drink per day for women and more than two drinks per day for men. The effects were derived 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 is randomly distributed. In the panel on the left, contact social distance refers to closest social distance (or degree of separation) between the contact and principal (e.g. direct friend = distance 1, friend's friend = distance 2, etc.). In the panel on the right, we ranked all physical distances between homes of directly connected principals and contacts (i.e., just those pairs at one degree of separation) and created six equally sized groups (1 = closest, 6 = farthest). The average distances for these six groups are: 1 = 0 miles; 2 = 0.26 miles; 3 = 1.5 miles; 4 = 3.4 miles; 5 = 9.3 miles; and 6 = 471 miles. There is no trend across physical distance. The bottom panels show the same kinds of analyses for the effect of abstaining contacts on the probability that principal abstains.
Effect of Heavy Drinking and Abstaining Contacts on Principals in the Framingham Social NetworkThis plot shows that future alcohol consumption behavior is positively associated with the fraction of friends and family who are heavy drinkers (red line) and negatively associated with the fraction of friends and family in the previous exam that are abstainers (blue line). Both lines based on bivariate LOESS regression, and dotted lines indicate 95% confidence intervals.
LLM interpretation
This figure consists of two bivariate LOESS regression plots showing the relationship between a principal's future alcohol consumption and their social network. The left plot shows a positive correlation between the "Principal's Drinks per Day at Next Exam" and the "Percent of Contacts Who Drink Heavily" (red line). The right plot shows a negative correlation between the same outcome and the "Percent of Contacts Who Abstain" (blue line). Both plots include dotted lines representing 95% confidence intervals.
Contact Type and Drinking in the Framingham Social NetworkThis graph shows the change in principal alcohol consumption behavior given contact alcohol consumption behavior. The left panel focuses on heavy drinking (more than one drink per day for women and more than two drinks per day for men) and the right panel focuses on abstention. Estimates based on generalized estimating equation logit models of drinking on several different sub-samples of the Framingham Heart Study Social Network. The dependent variable in each model is principal drinking status and independent variables include lagged principal drinking status, contact drinking status, lagged contact drinking status, principal age, gender, and education, and fixed effects for each wave. Full models and equations are available in the appendix. Mean effect sizes and Bonferroni-corrected 95% confidence intervals were calculated by simulating first difference in contact contemporaneous drinking (changing from 0 to 1) using 1,000 randomly drawn sets of estimates from coefficient covariance matrix and assuming all other variables are held at their means.
LLM interpretation
This figure consists of two forest plots showing the increase in probability of a principal's drinking behavior based on a contact's behavior across different relationship types. The left panel displays the probability of the principal drinking heavily if the contact drinks heavily, while the right panel shows the probability of the principal abstaining if the contact abstains. Both plots feature a vertical dashed line at 0%, with blue dots representing mean effect sizes and horizontal lines representing Bonferroni-corrected 95% confidence intervals.
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