Causal Inference in Studying the Long-Term Health Effects of Disasters: Challenges and Potential Solutions.

ABSTRACT: Two frequently encountered but underrecognized challenges for causal inference in studying the long-term health effects of disasters among survivors include 1) time-varying effects of disasters on a time-to-event outcome and 2) selection bias due to selective attrition. In this paper, we review approaches for overcoming these challenges and demonstrate application of the approaches to a real-world longitudinal data set of older adults who were directly affected by the 2011 Great East Japan Earthquake and Tsunami (n = 4,857). To illustrate the problem of time-varying effects of disasters, we examined the association between degree of damage due to the tsunami and all-cause mortality. We compared results from Cox regression analysis assuming proportional hazards with those derived using adju

SUBMITTER: Shiba K 

PROVIDER: S-EPMC8579004 | biostudies-literature | 2021 Sep

REPOSITORIES: biostudies-literature