Dynamic spread of happiness in a large social network: longitudinal analysis over 20 years in the Framingham Heart Study -- Fowler and Christakis 337: a2338 -- BMJ
- ISSN: 0959-8138
- DOI: 10.1136/bmj.a2338
Published 4 December 2008, doi:10.1136/bmj.a2338\nCite this as: BMJ 2008;337:a2338\nResearch\nDynamic spread of happiness in a large social network: longitudinal analysis over 20 years in the Framingham Heart Study\n\nJames H Fowler, associate professor1, Nicholas A Christakis, professor2\n\n1 Department of Political Science, University of California, San Diego, CA, USA , 2 Department of Health Care Policy, Harvard Medical School, and Department of Sociology, Harvard University, Cambridge, MA, USA\n\nCorrespondence to: N A Christakis firstname.lastname@example.org\nObjectives To evaluate whether happiness can spread from person to person and whether niches of happiness form within social networks.\n\nDesign Longitudinal social network analysis.\n\nSetting Framingham Heart Study social network.\n\nParticipants 4739 individuals followed from 1983 to 2003.\n\nMain outcome measures Happiness measured with validated four item scale; broad array of attributes of social networks and diverse social ties.\n\nResults Clusters of happy and unhappy people are visible in the network, and the relationship between people’s happiness extends up to three degrees of separation (for example, to the friends of one’s friends’ friends). People who are surrounded by many happy people and those who are central in the network are more likely to become happy in the future. Longitudinal statistical models suggest that clusters of happiness result from the spread of happiness and not just a tendency for people to associate with similar individuals. A friend who lives within a mile (about 1.6 km) and who becomes happy increases the probability that a person is happy by 25% (95% confidence interval 1% to 57%). Similar effects are seen in coresident spouses (8%, 0.2% to 16%), siblings who live within a mile (14%, 1% to 28%), and next door neighbours (34%, 7% to 70%). Effects are not seen between coworkers. The effect decays with time and with geographical separation.\n\nConclusions People’s happiness depends on the happiness of others with whom they are connected. This provides further justification for seeing happiness, like health, as a collective phenomenon.