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Effect of the 2010 Chilean Earthquake on Posttraumatic Stress: Reducing Sensitivity to Unmeasured Bias Through Study Design

Zubizarreta, José R.a; Cerdá, Magdalenab; Rosenbaum, Paul R.a

doi: 10.1097/EDE.0b013e318277367e

In 2010, a magnitude 8.8 earthquake hit Chile, devastating parts of the country. Having just completed its national socioeconomic survey, the Chilean government reinterviewed a subsample of respondents, creating unusual longitudinal data about the same persons before and after a major disaster. The follow-up evaluated posttraumatic stress symptoms (PTSS) using Davidson’s Trauma Scale. We use these data with two goals in mind. Most studies of PTSS after disasters rely on recall to characterize the state of affairs before the disaster. We are able to use prospective data on preexposure conditions, free of recall bias, to study the effects of the earthquake. Second, we illustrate recent developments in statistical methodology for the design and analysis of observational studies. In particular, we use new and recent methods for multivariate matching to control 46 covariates that describe demographic variables, housing quality, wealth, health, and health insurance before the earthquake. We use the statistical theory of design sensitivity to select a study design with findings expected to be insensitive to small or moderate biases from failure to control some unmeasured covariate. PTSS were dramatically but unevenly elevated among residents of strongly shaken areas of Chile when compared with similar persons in largely untouched parts of the country. In 96% of exposed-control pairs exhibiting substantial PTSS, it was the exposed person who experienced stronger symptoms (95% confidence interval = 0.91–1.00).

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From the aDepartment of Statistics, The Wharton School, University of Pennsylvania, Philadelphia, PA; and bDepartment of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY.

Submitted 14 March 2012; accepted 27 July 2012.

Partly supported by a grant from the Measurement, Methodology and Statistics Program of the U.S. National Science Foundation.

The authors report no conflicts of interest.

Supplemental digital content is available through direct URL citations in the HTML and PDF versions of this article ( This content is not peer-reviewed or copy-edited; it is the sole responsibility of the author.

A commentary on this article appears on page 88.

Correspondence: José R. Zubizarreta, Department of Statistics, The Wharton School, University of Pennsylvania, 3730 Walnut Street, 431-3 JMHH, Philadelphia, PA 19104-6340. E-mail:

© 2013 Lippincott Williams & Wilkins, Inc.