Citation

Pantell M, Rehkopf D, Jutte D, Syme SL, Balmes J, Adler N. Am. J. Public Health 2013; 103(11): 2056-2062.

Affiliation

Matthew Pantell is with the University of California, Berkeley-University of California, San Francisco Joint Medical Program, San Francisco. David Rehkopf is with the Stanford University School of Medicine, Stanford, CA. Douglas Jutte and S. Leonard Syme are with the School of Public Health, University of California, Berkeley. John Balmes is with the School of Public Health, University of California, Berkeley, and the School of Medicine, University of California, San Francisco. Nancy Adler is with the School of Medicine, University of California, San Francisco.

Copyright

(Copyright © 2013, American Public Health Association)

DOI

10.2105/AJPH.2013.301261

PMID

24028260

Abstract

Objectives. We explored the relationship between social isolation and mortality in a nationally representative US sample and compared the predictive power of social isolation with that of traditional clinical risk factors. Methods. We used data on 16 849 adults from the Third National Health and Nutrition Examination Survey and the National Death Index. Predictor variables were 4 social isolation factors and a composite index. Comparison predictors included smoking, obesity, elevated blood pressure, and high cholesterol. Unadjusted Kaplan-Meier tables and Cox proportional hazards regression models controlling for sociodemographic characteristics were used to predict mortality. Results. Socially isolated men and women had worse unadjusted survival curves than less socially isolated individuals. Cox models revealed that social isolation predicted mortality for both genders, as did smoking and high blood pressure. Among men, individual social predictors included being unmarried, participating infrequently in religious activities, and lacking club or organization affiliations; among women, significant predictors were being unmarried, infrequent social contact, and participating infrequently in religious activities. Conclusions. The strength of social isolation as a predictor of mortality is similar to that of well-documented clinical risk factors. Our results suggest the importance of assessing patients' level of social isolation. (Am J Public Health. Published online ahead of print September 12, 2013: e1-e7. doi:10.2105/AJPH.2013.301261).

Language: en