ArticleAmerican journal of epidemiology2021
Causal Inference in Studying the Long-Term Health Effects of Disasters: Challenges and Potential Solutions.
Article in American journal of epidemiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled it.
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Who cites it
16 citing papers in PubMed, 1 synthesis or guideline pooled it, 25 citations in OpenAlex.
- Long-term mental health trajectories after the Great East Japan Earthquake: a systematic review.European journal of psychotraumatology · 2025Pooled it
- Stressful exposure from the 2004 Indian Ocean Tsunami drives long-term changes in thyroid hormone physiology.bioRxiv : the preprint server for biology · 2026Article
- Disaster-related home loss, mental health, and risk of cognitive disability: causal mediation analysis using longitudinal data of disaster survivors.American journal of epidemiology · 2025Article
- Exposing the loci of bias: a taxonomical exploration of sources of bias in population mental health research.Population health metrics · 2025Review
- Resilience Factors Affecting Long-Term Trajectories of Depressive Symptoms in the Aftermath of the Great East Japan Earthquake and Tsunami Among Older Adults.The journals of gerontology. Series B, Psychological sciences and social sciences · 2025Article
- Association of disaster-related damage with inflammatory diet among older survivors of the Great East Japan Earthquake and Tsunami.The British journal of nutrition · 2024Article
- Do Adverse Childhood Experiences Modify the Association Between Disaster-Related Trauma and Cognitive Disability?American journal of epidemiology · 2024Article
- Does disaster-related relocation impact mental health via changes in group participation among older adults? Causal mediation analysis of a pre-post disaster study of the 2016 Kumamoto earthquake.BMC public health · 2023Article
- Article
- Uncovering Heterogeneous Associations Between Disaster-Related Trauma and Subsequent Functional Limitations: A Machine-Learning Approach.American journal of epidemiology · 2023Article
- Long-Term Associations between Disaster-Related Home Loss and Health and Well-Being of Older Survivors: Nine Years after the 2011 Great East Japan Earthquake and Tsunami.Environmental health perspectives · 2022Article
- Early childhood adversity and late-life depressive symptoms: unpacking mediation and interaction by adult socioeconomic status.Social psychiatry and psychiatric epidemiology · 2022Article
- Long-Term Health Impacts of Wildfire Exposure: A Retrospective Study Exploring Hospitalization Dynamics Following the 2016 Wave of Fires in Israel.International journal of environmental research and public health · 2022Article
- Long-Term Trend in the Association Between Disaster Damage and Happiness Before and After the Great East Japan Earthquake.International journal of public health · 2022Article
- Heterogeneity in cognitive disability after a major disaster: A natural experiment study.Science advances · 2021Article
- Using Propensity Scores for Causal Inference: Pitfalls and Tips.Journal of epidemiology · 2021Article
Corrections and comments
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Authors and funding
8 authors.
Funding
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 adjusted parametric survival curves allowing for time-varying hazard ratios. To illustrate the problem of selection bias, we examined the association between proximity to the coast (a proxy for housing damage from the tsunami) and depressive symptoms. We corrected for selection bias due to attrition in the 2 postdisaster follow-up surveys (conducted in 2013 and 2016) using multivariable adjustment, inverse probability of censoring weighting, and survivor average causal effect estimation. Our results demonstrate that analytical approaches which ignore time-varying effects on mortality and selection bias due to selective attrition may underestimate the long-term health effects of disasters.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.