Neither author has a dependent relationship with any of the funding agencies - R-Shiksha Trust

Neither author has a dependent relationship with any of the funding agencies

Neither author has a dependent relationship with any of the funding agencies

What this study adds

Happiness is a network phenomenon, clustering in groups of people that extend up to three degrees of ple, to one’s friends’ friends’ friends)

Footnotes

We thank Laurie Meneades, Rebecca Joyce, Molly Collins, Marian Bellwood, and Karen Mutalik for the expert assistance required to build the analytical data. We thank Chris Dawes, Dan Gilbert, Tom Keegan, Erez Lieberman, Andrew Oswald, Mark Pachucki, and Holly Shakya for helpful suggestions regarding the manuscript.

Contributors: Both authors participated in the conception and design of the study, analysis and interpretation of data, drafting and revising the article, and its final approval. Both authors are guarantors.

Funding: This was work was supported by NIH (R-01 AG24448, P-01 AG031093) and by the Pioneer Portfolio of the Robert Wood Johnson Foundation; NHLBI’s Framingham Heart Study is supported by contract number N01-HC-25195.

Ethical approval: This work was approved by the Harvard institutional review board; the parent Framingham Heart Study has separate IRB approval. All participants gave informed consent.

This is an open-access article distributed under the terms of the Creative Commons Attribution Non-commercial License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Methods

The ascertainment of social ties in the Framingham Heart Study was wide and systematic. The study recorded complete information about all first order relatives (parents, spouses, siblings, children), whether alive or dead, and at least one close friend at up to seven examinations from 1971 to 2003. Detailed information on home address was also captured at each time point, which we geocoded to determine neighbour relationships. Specific information about place of employment at each wave allowed us to identify ties to coworkers within the network.

We studied 4739 of the 5124 egos who were alive in 1983 (which was the first time happiness was measured in the Framingham study). All participants were followed until 2003 (at exam 7), as were any ties to alters noted during the time period 1983-2003.

The main coefficient of interest in these regression models is the one related to contemporaneous happiness in alters-that is, the extent to which an alter’s present happiness, net of the alter’s previous happiness, is associated with an ego’s present happiness, net of the ego’s previous happiness.35 49 We used generalised estimating equation procedures to account for multiple observations of the same ego across waves and across ego-alter pairings.50 We assumed an independent working correlation structure for the clusters.51

Fig 2 Social distance and happiness in the Framingham social network. Percentage increase in likelihood an ego is happy if friend or family member at certain social distance is happy (instead of unhappy). The relationship is strongest between individuals who are directly connected but remains significantly >0 at social distances up to three degrees of separation, meaning that a person’s happiness is associated with happiness of people up to three degrees removed from them in the network. Values derived by comparing conditional probability of being happy in observed network with an identical network (with topology and incidence of happiness preserved) in which same number of happy people are randomly distributed. Alter social distance refers to closest social distance between alter and ego (alter=distance 1, alter’s alter=distance 2, etc). Error bars show 95% confidence intervals

Fig 4 Alter type and happiness in the Framingham social network. Friends, spouses, siblings, and neighbours significantly influence happiness, but only if they live close to ego. Effects estimated with generalised estimating equation logit models of happiness on several different subsamples of the network (see table S6 in appendix on bmj)

Finally, similarity in socioeconomic status probably cannot explain the clustering of happy people as next door neighbours have a much stronger influence than neighbours who live a few doors down in the same neighbourhood (and who consequently have similar housing, wealth, and environmental exposures). Moreover, the geographical distribution of happiness is not systematically related to local levels of either income or education (see maps in appendix on bmj). Both of these observations suggest that contextual effects are probably not driving our results.

There is of course a tradition of community approaches to mental health,57 58 but this longstanding concern is now being coupled with a burgeoning interest in health and social networks.59 More generally, conceptions of health and concerns for the wellbeing of both individuals and populations are increasingly broadening to include diverse “quality of life” attributes, including happiness. Most important from our perspective is the recognition that people are embedded in social networks and that the health and wellbeing of one person affects the health and wellbeing of others. This fundamental fact of existence provides a conceptual justification for the specialty of public health. Human happiness is not merely the province of isolated individuals.

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