Evidence map›Paper›PMID 40752514›Full record

ArticleThe Lancet. Planetary health2025

Severe flooding and cause-specific hospitalisation among older adults in the USA: a retrospective matched cohort analysis.

Sarika Aggarwal, Jie K Hu, Jonathan A Sullivan, Robbie M Parks, Rachel C Nethery

Abstract read
In one paragraph

Article in The Lancet. Planetary health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

5 authors.

Sarika AggarwalDepartment of Biostatistics, Harvard T H Chan School of Public Health, Boston, MA, USA. Electronic address: saggarwal@g.harvard.edu.
Jie K HuDepartment of Statistics, The Ohio State University, Columbus, OH, USA.
Jonathan A SullivanNelson Institute for Environmental Studies, University of Wisconsin-Madison, Madison, WI, USA.
Robbie M ParksDepartment of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, NY, USA.
Rachel C NetheryDepartment of Biostatistics, Harvard T H Chan School of Public Health, Boston, MA, USA.

Funding

Translational Research Support CoreP30ES000002 · NIEHS · HARVARD UNIVERSITY (SCH OF PUBLIC HLTH) · PI JAIME ELIZABETH HART · 1985 to 2026
$44.6M
Training Program in Environmental EpidemiologyT32ES007069 · NIEHS · HARVARD UNIVERSITY (SCH OF PUBLIC HLTH) · PI LADEN, FRANCINE · 1985 to 2024
$13.9M
GRADUATE TRAINING IN BIOSTATISTICST32ES007142 · NIEHS · HARVARD UNIVERSITY (SCH OF PUBLIC HLTH) · PI Brent Andrew Coull · 1985 to 2026
$11.9M
Novel Assessments of the Health Impacts of Tropical CyclonesR00ES033742 · NIEHS · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI PARKS, ROBBIE M · 2023 to 2025
$911k
Causal machine learning methods for studying the effects of environmental exposures on childhood cancer using natural experimentsK01ES032458 · NIEHS · HARVARD SCHOOL OF PUBLIC HEALTH · PI NETHERY, RACHEL C · 2021 to 2023
$417k
NIEHS NIH HHS K01 ES032458NIEHS NIH HHS P30 ES000002NIEHS NIH HHS R00 ES033742NIEHS NIH HHS T32 ES007069NIEHS NIH HHS T32 ES007142
6 · The paper itself

Abstract

backgroundFloods are the most common climate-related disaster; yet previous studies have investigated the impact of floods on only a few health outcomes in narrow spatiotemporal settings. We aimed to assess the association between severe flood exposure and cause-specific hospitalisation rates in adults older than 65 years in the contiguous USA.

methodsIn this retrospective matched cohort analysis, we obtained inpatient claims data from Medicare fee-for-service beneficiaries older than 65 years living in the contiguous USA from Jan 1, 2000, to Dec 31, 2016. From each inpatient hospitalisation record, we extracted the admission date, primary International Classification of Diseases, 9th revision, clinical modification (ICD-9-CM) code (or 10th revision [ICD-10-CM] code on or after Oct 1, 2015), and self-reported residential ZIP code. Hospitalisation data were linked with satellite-based, high-resolution historical flood maps from the Global Flood Database by ZIP code. Days during and shortly after a flood exposure were matched to non-flood-affected control days by ZIP code and day-of-year. We estimated relative percentage changes in hospitalisation rates for 13 mutually exclusive, well-defined disease categories during and in the 4 weeks following flood exposure with conditional quasi-Poisson regression models.

findingsThis study captured 72 major flood events and included over 4·5 million hospitalisations occurring over a 17-year period. We observed elevated rates of hospitalisation on average during and following flood exposure for skin diseases (3·1% [95% CI 1·4 to 4·9]), nervous system diseases (2·5% [1·0 to 4·1]), musculoskeletal system diseases (1·3% [0·3 to 2·3]), and injuries or poisoning (1·1% [0·2 to 2·0]). Communities with lower proportions of Black residents experienced exacerbated flood effects for nervous system diseases (7·6% [95% CI 2·8 to 12·6]), whereas skin diseases (6·1% [1·9 to 10·5]) and mental health-related impacts (3·0% [-0·3 to 6·5]) were more pronounced for areas with larger percentages of Black residents during flood exposure.

interpretationAmong adults older than 65 years, exposure to severe flood events was associated with increased hospitalisation rates for skin diseases, nervous system diseases, musculoskeletal system diseases, and injuries. Different patterns of hospital admission persisted for populations with higher versus lower proportions of Black residents. Our findings indicate a need for targeted flood-specific preparedness and adaptation strategies for socially vulnerable populations, including older individuals and racially minoritised communities.

fundingNational Institutes of Health, Harvard Data Science Initiative, and Alfred P Sloan Foundation.

Indexed as

FloodsHospitalizationAgedAged, 80 and overFemaleHumansMaleRetrospective StudiesUnited States

Identifiers

PMID40752514
PMCPMC12360453

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LicenceCC BY
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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.