Evidence map›Paper›PMID 37793693›Full record

ArticleBMJ (Clinical research ed.)2023

Mortality risks associated with floods in 761 communities worldwide: time series study.

Zhengyu Yang, Wenzhong Huang, Joanne E McKenzie, Rongbin Xu, Pei Yu, Tingting Ye, Bo Wen, Antonio Gasparrini, Ben Armstrong, Shilu Tong and 6 more

Open access · hybridAbstract read
In one paragraph

Article in BMJ (Clinical research ed.), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.

0numbers the graph read from it
0cells of the map it votes in
30citing papers in PubMed
9.7field-weighted citation impact, top 1% of its field
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

30 citing papers in PubMed, 62 citations in OpenAlex.

  1. Article
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  7. Attitudes toward climate change risk among older people: new evidence from the English Longitudinal Study of Ageing.The journals of gerontology. Series B, Psychological sciences and social sciences · 2026
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  14. Disaster preparedness and kidney health in children.Pediatric nephrology (Berlin, Germany) · 2025
    Review
  15. Article
  16. Article
  17. All-cause excess mortality following Storm Daniel flood event in Greece.Journal of public health (Oxford, England) · 2025
    Article
  18. Article
  19. Article
  20. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

16 authors at 6 institutions in 7 countries.

Zhengyu YangSchool of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, 3004, Australia.
Wenzhong HuangSchool of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, 3004, Australia.
Joanne E McKenzieSchool of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, 3004, Australia.
Rongbin XuSchool of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, 3004, Australia.
Pei YuSchool of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, 3004, Australia.
Tingting YeSchool of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, 3004, Australia.
Bo WenSchool of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, 3004, Australia.
Antonio GasparriniDepartment of Public Health Environments and Society, London School of Hygiene and Tropical Medicine, London, UK.
Ben ArmstrongDepartment of Public Health Environments and Society, London School of Hygiene and Tropical Medicine, London, UK.
Shilu TongSchool of Public Health and Social Work, Queensland University of Technology, Brisbane, QLD, Australia.
Eric LavigneSchool of Epidemiology and Public Health, Faculty of Medicine, University of Ottawa, Ottawa, ON, Canada.
Joana MadureiraDepartment of Geography, University of Santiago de Compostela, Santiago de Compostela, Spain.
Jan KyselýInstitute of Atmospheric Physics, Czech Academy of Sciences, Prague, Czech Republic.
Yuming GuoSchool of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, 3004, Australia.ORCID 0000-0002-1766-6592
Shanshan LiSchool of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, 3004, Australia shanshan.li@monash.edu.ORCID 0000-0002-9021-8470
MCC Collaborative Research Network
Monash University · AURoyal Society of Tropical Medicine and Hygiene · GBCzech University of Life Sciences Prague · CZHealth Canada · CAQueensland University of Technology · AUUniversidade de Santiago de Compostela · ES

Funding

Medical Research Council MR/V034162/1
6 · The paper itself

Abstract

objectiveTo evaluate lag-response associations and effect modifications of exposure to floods with risks of all cause, cardiovascular, and respiratory mortality on a global scale.

designTime series study.

setting761 communities in 35 countries or territories with at least one flood event during the study period.

participantsMulti-Country Multi-City Collaborative Research Network database, Australian Cause of Death Unit Record File, New Zealand Integrated Data Infrastructure, and the International Network for the Demographic Evaluation of Populations and their Health Network database.

main outcome measuresThe main outcome was daily counts of deaths. An estimation for the lag-response association between flood and daily mortality risk was modelled, and the relative risks over the lag period were cumulated to calculate overall effects. Attributable fractions of mortality due to floods were further calculated. A quasi-Poisson model with a distributed lag non-linear function was used to examine how daily death risk was associated with flooded days in each community, and then the community specific associations were pooled using random effects multivariate meta-analyses. Flooded days were defined as days from the start date to the end date of flood events.

resultsA total of 47.6 million all cause deaths, 11.1 million cardiovascular deaths, and 4.9 million respiratory deaths were analysed. Over the 761 communities, mortality risks increased and persisted for up to 60 days (50 days for cardiovascular mortality) after a flooded day. The cumulative relative risks for all cause, cardiovascular, and respiratory mortality were 1.021 (95% confidence interval 1.006 to 1.036), 1.026 (1.005 to 1.047), and 1.049 (1.008 to 1.092), respectively. The associations varied across countries or territories and regions. The flood-mortality associations appeared to be modified by climate type and were stronger in low income countries and in populations with a low human development index or high proportion of older people. In communities impacted by flood, up to 0.10% of all cause deaths, 0.18% of cardiovascular deaths, and 0.41% of respiratory deaths were attributed to floods.

conclusionsThis study found that the risks of all cause, cardiovascular, and respiratory mortality increased for up to 60 days after exposure to flood and the associations could vary by local climate type, socioeconomic status, and older age.

Indexed as

FloodsRespiratory Tract DiseasesAgedAustraliaClimateHumansMortalityTime Factors

Identifiers

PMID37793693
PMCPMC10548259
OpenAlexW4387328023

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

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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.