Original Article

Molecular Psychiatry (2011) 16, 273–281; doi:10.1038/mp.2010.13; published online 16 March 2010

Social network determinants of depression

J N Rosenquist1,2, J H Fowler3 and N A Christakis4,5

  1. 1Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA
  2. 2Department of Health Care Policy, Harvard Medical School, Boston, MA, USA
  3. 3Department of Political Science, University of California, San Diego, CA, USA
  4. 4Department of Health Care Policy, Harvard Medical School, Cambridge, MA, USA
  5. 5Department of Sociology, Harvard University, Cambridge, MA, USA

Correspondence: Dr JN Rosenquist, Health Care Policy, Harvard Medical School, 180 Longwood Avenue, Boston, MA 02115, USA. E-mail: jrosenqu@gmail.com

Received 29 May 2009; Revised 26 December 2009; Accepted 27 December 2009; Published online 16 March 2010.

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Abstract

The etiology of depression has long been thought to include social environmental factors. To quantitatively explore the novel possibility of person-to-person spread and network-level determination of depressive symptoms, analyses were performed on a densely interconnected social network of 12067 people assessed repeatedly over 32 years as part of the Framingham Heart Study. Longitudinal statistical models were used to examine whether depressive symptoms in one person were associated with similar scores in friends, co-workers, siblings, spouses and neighbors. Depressive symptoms were assessed using CES-D scores that were available for subjects in three waves measured between 1983 and 2001. Results showed both low and high CES-D scores (and classification as being depressed) in a given period were strongly correlated with such scores in one's friends and neighbors. This association extended up to three degrees of separation (to one's friends’ friends’ friends). Female friends appear to be especially influential in the spread of depression from one person to another. The results are robust to multiple network simulation and estimation methods, suggesting that network phenomena appear relevant to the epidemiology of depression and would benefit from further study.

Keywords:

depression; social networks; sociology; social norms; mood