Evidence map›Paper›PMID 33716382›Full record

ArticleJournal of the Royal Society of New Zealand2020

Disaster Resilience in Aging Populations: Lessons from the 2011 Great East Japan Earthquake & Tsunami.

Ichiro Kawachi, Jun Aida, Hiroyuki Hikichi, Katsunori Kondo

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of the Royal Society of New Zealand, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

19 citing papers in PubMed.

  1. Article
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  3. Social cohesion, social capital and mental health: current evidence and future research directions.World psychiatry : official journal of the World Psychiatric Association (WPA) · 2026
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Ichiro KawachiHarvard University.
Jun AidaTohoku University Graduate School of Dentistry.
Hiroyuki HikichiHarvard University.
Katsunori KondoChiba University Graduate School of Medicine.

Funding

Impact of social cohesion on functional recovery after earthquake and tsunamiR01AG042463 · NIA · HARVARD SCHOOL OF PUBLIC HEALTH · PI KAWACHI, ICHIRO · 2013 to 2022
$4.9M
NIA NIH HHS R01 AG042463
6 · The paper itself

Abstract

Recovery after major disaster poses a unique set of challenges for the older population, including disruption of medical care for pre-existing conditions, functional limitations that impede recovery, and social isolation following involuntary resettlement. In this review, we summarize the lessons about disaster resilience that have been learned (so far) from a unique ongoing field study based in a community that was affected by the 2011 earthquake and tsunami in Japan. In the Iwanuma Study, baseline information about the health status and living conditions of older residents was collected seven months before the disaster. A follow-up survey was conducted 2.5 years after the disaster, allowing us investigate the risk and protective factors for a range of disaster-related health sequelae, including mental illness and cognitive disability. A consistent finding to emerge from our studies is the critical role of social connections (the "social capital" of a community) in protecting against the deleterious after-effects of psychological trauma and involuntary resettlement following the disaster. In contrast to the emphasis on investing in material infrastructure to prepare for disasters, a review of our studies suggests that repairing (or at least preserving) the social fabric of people's lives is a crucial ingredient in disaster resilience.

Indexed as

agingdementiaDisaster resiliencesocial capital

Identifiers

PMID33716382
PMCPMC7954223

What OpenQuestion holds

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Registered trials

None linked

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.