Happiness really does rub off—a person's happiness depends on the happiness of others with whom they are connected, finds research published on bmj.com today.
Happiness is not just an individual experience or choice, but is dependent on the happiness of others to whom individuals are connected directly and indirectly, and requires close proximity to spread, say the authors. For example, a friend who becomes happy and lives within a mile increases your likelihood of happiness by 25%.
Professor Nicholas Christakis from Harvard Medical School and Professor James Fowler from the University of California, San Diego, analysed data collected in the Framingham Heart Study to find out if happiness can spread from person to person and if clusters of happiness form within social networks*.
In the Framingham Heart Study** 5,124 adults aged 21-70 were recruited and followed between 1971 and 2003, to examine various aspects of their life and health. Participants were asked to identify their relatives, "close friends," place of residence, and place of work to ensure they could be contacted every two to four years for follow-up. The authors found 53,228 social ties between the 5,124 participants and a total of 12,067 people. They focused on 4,739 people followed from 1983 to 2003.
Additional data on mental health, collected using a depression rating scale during the original study, recorded agreement or disagreement with four statements "I felt hopeful about the future," "I was happy," "I enjoyed life," "I felt that I was just as good as other people." In this BMJ paper, the authors defined happiness as a perfect score for all four statements.
Using statistical analysis the researchers measured how social networks were correlated with reported happiness. They found that live-in partners who become happy increase the likelihood of their partner being happy by 8%, similar effects were seen for siblings who live close by (14%) and neighbours (34%). Work colleagues did not affect happiness levels suggesting that social context may curtail the spread of emotional states.
Interestingly, it is not only immediate social ties that have an impact on happiness levels, the relationship between people's happiness can extend up to three degrees of separation (to the friend of one's friends' friend). Indeed, people who are surrounded by happy people are likely to become happy in the future.
Importantly, they report that close physical proximity is essential for happiness to spread. A person is 42% more likely to be happy if a friend who lives less than half a mile away becomes happy, the effect is only 22% for friends who live less than two miles away, and this effect declines and becomes insignificant at greater distances.
The findings suggest that clusters of happiness result from the spread of happiness and not just a tendency for people to associate with similar individuals.
The authors say: "Changes in individual happiness can ripple through social networks and generate large scale structure in the network, giving rise to clusters of happy and unhappy individuals."
They conclude: "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 fundamental conceptual justification for the specialty of public health. Human happiness is not merely the province of isolated individuals."
In an accompanying editorial, Professor Andrew Steptoe from University College London and Professor Ana Diez Roux from University of Michigan School of Public Health, say that the study is "groundbreaking": "If, [as these findings suggest] happiness is indeed transmitted through social connections, it could indirectly contribute to the social transmission of health", and has serious implications for the design of policies and interventions.
However, in another research paper, Jason Fletcher from Yale University and Ethan Cohen-Cole from the Federal Reserve Bank of Boston, caution that the methods used to detect social network effects in Christakis and Fowler's study are subject to "potentially large biases…that might produce effects where none exist."
They examined whether network effects can be detected for three health outcomes—headaches, skin problems, and height. They found that, for example, a friend's acne problems increased the likelihood of an individual's acne problems and that the likelihood that an individual had headaches also increased with the presence of a friend with headaches. But after controlling for environmental confounders these social network effects disappeared. They conclude: "These methods might produce premature claims of social network effects in health outcomes."
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