Evidence map›Paper›PMID 34175888›Full record

ArticleJournal of exposure science & environmental epidemiology2021

The Texas flood registry: a flexible tool for environmental and public health practitioners and researchers.

Marie Lynn Miranda, Rashida Callender, Joally M Canales, Elena Craft, Katherine B Ensor, Max Grossman, Loren Hopkins, Jocelyn Johnston, Umair Shah, Joshua Tootoo

Abstract read
In one paragraph

Article in Journal of exposure science & environmental epidemiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Article
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  8. Article
  9. Exposure science perspective on disaster preparedness and resilience.Journal of exposure science & environmental epidemiology · 2021
    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

10 authors.

Marie Lynn MirandaChildren's Environmental Health Initiative, University of Notre Dame, South Bend, IN, USA. mlm@nd.edu.
Rashida CallenderChildren's Environmental Health Initiative, Rice University, Houston, TX, USA.
Joally M CanalesChildren's Environmental Health Initiative, Rice University, Houston, TX, USA.
Elena CraftEnvironmental Defense Fund, Austin, TX, USA.
Katherine B EnsorDepartment of Statistics, Rice University, Houston, TX, USA.
Max GrossmanChildren's Environmental Health Initiative, University of Notre Dame, South Bend, IN, USA.
Loren HopkinsDepartment of Statistics, Rice University, Houston, TX, USA.
Jocelyn JohnstonChildren's Environmental Health Initiative, University of Notre Dame, South Bend, IN, USA.
Umair ShahHarris County Public Health, Houston, TX, USA.
Joshua TootooChildren's Environmental Health Initiative, University of Notre Dame, South Bend, IN, USA.

Funding

Time Sensitive Award Mechanism - Using Exposure Science to Identify Populations at Risk in the Aftermath of Hurricane Harvey: administrative supplementR21ES029461 · NIEHS · RICE UNIVERSITY · PI MIRANDA, MARIE LYNN · 2018 to 2020
$1.2M
NIEHS NIH HHS R21 ES029461
6 · The paper itself

Abstract

backgroundMaking landfall in Rockport, Texas in August 2017, Hurricane Harvey resulted in unprecedented flooding, displacing tens of thousands of people, and creating environmental hazards and exposures for many more.

objectiveWe describe a collaborative project to establish the Texas Flood Registry to track the health and housing impacts of major flooding events.

methodsThose who enroll in the registry answer retrospective questions regarding the impact of storms on their health and housing status. We recruit both those who did and did not flood during storm events to enable key comparisons. We leverage partnerships with multiple local health departments, community groups, and media outlets to recruit broadly. We performed a preliminary analysis using multivariable logistic regression and a binomial Bayesian conditional autoregressive (CAR) spatial model.

resultsWe find that those whose homes flooded, or who came into direct skin contact with flood water, are more likely to experience a series of self-reported health effects. Median household income is inversely related to adverse health effects, and spatial analysis provides important insights within the modeling approach. SIGNIFICANCE: Global climate change is likely to increase the number and intensity of rainfall events, resulting in additional health burdens. Population-level data on the health and housing impacts of major flooding events is imperative in preparing for our planet's future.

Indexed as

FloodsPublic HealthBayes TheoremHumansRegistriesRetrospective StudiesTexasAir pollution, Climate change, Geospatial Analyses

Identifiers

PMID34175888
PMCPMC8234769

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.