Evidence map›Paper›PMID 38715068›Full record

ArticleBMC medicine2024

Floods and cause-specific mortality in the UK: a nested case-control study.

Yao Wu, Danijela Gasevic, Bo Wen, Zhengyu Yang, Pei Yu, Guowei Zhou, Yan Zhang, Jiangning Song, Hong Liu, Shanshan Li and 1 more

Abstract read
In one paragraph

Article in BMC medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
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

11 authors.

Yao WuSchool of Public Health and Preventive Medicine, Monash University, Level 2, 553 St Kilda Road, Melbourne, VIC, 3004, Australia.
Danijela GasevicSchool of Public Health and Preventive Medicine, Monash University, Level 2, 553 St Kilda Road, Melbourne, VIC, 3004, Australia.
Bo WenSchool of Public Health and Preventive Medicine, Monash University, Level 2, 553 St Kilda Road, Melbourne, VIC, 3004, Australia.
Zhengyu YangSchool of Public Health and Preventive Medicine, Monash University, Level 2, 553 St Kilda Road, Melbourne, VIC, 3004, Australia.
Pei YuSchool of Public Health and Preventive Medicine, Monash University, Level 2, 553 St Kilda Road, Melbourne, VIC, 3004, Australia.
Guowei ZhouDepartment of Dermatology, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, China.
Yan ZhangDepartment of Dermatology, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, China.
Jiangning SongDepartment of Biochemistry and Molecular Biology, Monash Biomedicine Discovery Institute, Monash University, Melbourne, VIC, 3800, Australia.
Hong Liu *Department of Dermatology, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, China.
Shanshan Li *Department of Dermatology, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, China.
Yuming Guo *Department of Dermatology, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, China. yuming.guo@monash.edu.ORCID 0000-0002-1766-6592

Funding

Australian Research Council DP210102076China Scholarship Council 201906210065China Scholarship Council 202006010043China Scholarship Council 202006010044National Health and Medical Research Council GNT1163693National Health and Medical Research Council GNT2000581National Health and Medical Research Council GNT2008813National Health and Medical Research Council GNT2009866
6 · The paper itself

Abstract

backgroundFloods are the most frequent weather-related disaster, causing significant health impacts worldwide. Limited studies have examined the long-term consequences of flooding exposure.

methodsFlood data were retrieved from the Dartmouth Flood Observatory and linked with health data from 499,487 UK Biobank participants. To calculate the annual cumulative flooding exposure, we multiplied the duration and severity of each flood event and then summed these values for each year. We conducted a nested case-control analysis to evaluate the long-term effect of flooding exposure on all-cause and cause-specific mortality. Each case was matched with eight controls. Flooding exposure was modelled using a distributed lag non-linear model to capture its nonlinear and lagged effects.

resultsThe risk of all-cause mortality increased by 6.7% (odds ratio (OR): 1.067, 95% confidence interval (CI): 1.063-1.071) for every unit increase in flood index after confounders had been controlled for. The mortality risk from neurological and mental diseases was negligible in the current year, but strongest in the lag years 3 and 4. By contrast, the risk of mortality from suicide was the strongest in the current year (OR: 1.018, 95% CI: 1.008-1.028), and attenuated to lag year 5. Participants with higher levels of education and household income had a higher estimated risk of death from most causes whereas the risk of suicide-related mortality was higher among participants who were obese, had lower household income, engaged in less physical activity, were non-moderate alcohol consumers, and those living in more deprived areas.

conclusionsLong-term exposure to floods is associated with an increased risk of mortality. The health consequences of flooding exposure would vary across different periods after the event, with different profiles of vulnerable populations identified for different causes of death. These findings contribute to a better understanding of the long-term impacts of flooding exposure.

Indexed as

FloodsAdultAgedCase-Control StudiesCause of DeathFemaleHumansMaleMiddle AgedRisk FactorsUnited KingdomFloodsLong-termMortalityNatural disaster

Identifiers

PMID38715068
PMCPMC11077877

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.