Evidence map›Paper›PMID 40417424›Full record

ArticleNature water2025

Hospitalization risks associated with floods in a multi-country study.

Zhengyu Yang, Wenzhong Huang, Joanne E McKenzie, Rongbin Xu, Pei Yu, Yao Wu, Yanming Liu, Bo Wen, Yiwen Zhang, Wenhua Yu and 14 more

Abstract read
In one paragraph

Article in Nature water, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 pooled it
–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

7 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Review
  4. Article
  5. Article
  6. Article
  7. Review
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

24 authors.

Zhengyu YangClimate Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria Australia.ORCID 0000-0001-7291-4475
Wenzhong HuangClimate Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria Australia.ORCID 0000-0001-8871-1947
Joanne E McKenzieMethods in Evidence Synthesis Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria Australia.
Rongbin XuClimate Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria Australia.ORCID 0000-0003-1906-8614
Pei YuClimate Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria Australia.ORCID 0000-0002-7485-1751
Yao WuClimate Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria Australia.ORCID 0000-0002-8105-0522
Yanming LiuClimate Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria Australia.ORCID 0000-0001-8599-7118
Bo WenClimate Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria Australia.ORCID 0000-0001-8379-1730
Yiwen ZhangClimate Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria Australia.ORCID 0000-0001-9570-4147
Wenhua YuClimate Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria Australia.ORCID 0000-0002-4733-8610
Tingting YeClimate Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria Australia.ORCID 0000-0001-5405-7051
Yuxi ZhangSchool of Life and Environmental Sciences, University of Sydney, Sydney, New South Wales Australia.ORCID 0000-0002-0176-7620
Ke JuClimate Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria Australia.
Simon HalesDepartment of Public Health, University of Otago, Wellington, New Zealand.ORCID 0000-0002-4529-7595
Micheline de Sousa Zanotti Stagliorio CoelhoDepartment of Pathology, School of Medicine, University of São Paulo, São Paulo, Brazil.ORCID 0000-0002-9732-1278
Patricia MatusSchool of Medicine, University of the Andes (Universidad de los Andes), Las Condes, Chile.ORCID 0000-0003-1844-6564
Kraichat TantrakarnapaSocial and Environmental Medicine, Faculty of Tropical Medicine, Mahidol University, Krung Thep Maha Nakhon, Bangkok, Thailand.ORCID 0000-0003-1943-6202
Yue Leon GuoEnvironmental and Occupational Medicine, National Taiwan University College of Medicine and National Taiwan University Hospital, Taipei, Taiwan.ORCID 0000-0002-8530-4809
Wissanupong KliengchuaySocial and Environmental Medicine, Faculty of Tropical Medicine, Mahidol University, Krung Thep Maha Nakhon, Bangkok, Thailand.
Eric LavigneSchool of Epidemiology and Public Health, University of Ottawa, Ottawa, Ontario Canada.
Dung PhungSchool of Public Health, University of Queensland, Brisbane, Queensland Australia.ORCID 0000-0002-1615-3234
Paulo Hilario Nascimento SaldivaDepartment of Pathology, School of Medicine, University of São Paulo, São Paulo, Brazil.
Yuming GuoClimate Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria Australia.ORCID 0000-0002-1766-6592
Shanshan LiClimate Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria Australia.ORCID 0000-0002-9021-8470

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Floods of unprecedented intensity and frequency have been observed. However, evidence regarding the impacts of floods on hospitalization remains limited. Here we collected daily hospitalization counts during 2000-2019 from 747 communities in Australia, Brazil, Canada, Chile, New Zealand, Taiwan, Thailand and Vietnam. For each community, flooded days were defined as days from the start dates to the end dates of flood events. Lag-response associations between flooded day and daily hospitalization risks were estimated for each community using a quasi-Poisson regression model with a distributed lag nonlinear function. The community-specific estimates were then pooled using a random-effects meta-analysis. Based on the pooled estimates, attributable fractions of hospitalizations due to floods were calculated. We found that hospitalization risks increased and persisted for up to 210 days after flood exposure, with the overall relative risks being 1.26 (95% confidence interval 1.15-1.38) for all causes, 1.35 (1.21-1.50) for cardiovascular diseases, 1.30 (1.13-1.49) for respiratory diseases, 1.26 (1.10-1.44) for infectious diseases, 1.30 (1.17-1.45) for digestive diseases, 1.11 (0.98-1.25) for mental disorders, 1.61 (1.39-1.86) for diabetes, 1.35 (1.21-1.50) for injury, 1.34 (1.21-1.48) for cancer, 1.34 (1.20-1.50) for nervous system disorders and 1.40 (1.22-1.60) for renal diseases. The associations were modified by climate types, flood severity, age, population density and socioeconomic status. Flood exposure contributed to hospitalizations by up to 0.27% from all causes. This study revealed that flood exposure was associated with increased all-cause and ten cause-specific hospitalization risks within up to 210 days after exposure.

Indexed as

DiseasesHealth services

Identifiers

PMID40417424
PMCPMC12098117

What OpenQuestion holds

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LicenceCC BY
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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.