Evidence map›Paper›PMID 40550634›Full record

ArticleInjury prevention : journal of the International Society for Child and Adolescent Injury Prevention2025

Integrating spatial analysis with census data to unravel the complex interaction between socio-economic variables, the built environment and multiple housefires in a predominantly rural state.

Gilsu Pae, Alba Paulsen, Siri Pothula, Colette Galet, Lucy Ann Wibbenmeyer

Abstract read
In one paragraph

Article in Injury prevention : journal of the International Society for Child and Adolescent Injury Prevention, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Gilsu PaeDepartment of Epidemilogy, College of Public Health, University of Iowa, Iowa Health Care, Iowa City, IA, USA.ORCID 0000-0003-2980-5518
Alba PaulsenDepartment of Surgery, The University of Iowa, Iowa Health Care, Iowa City, Iowa, USA.
Siri PothulaUniversity of Illinois Chicago, Chicago, Illinois, USA.
Colette GaletDepartment of Surgery, The University of Iowa, Iowa Health Care, Iowa City, Iowa, USA.ORCID 0000-0002-5931-2143
Lucy Ann WibbenmeyerDepartment of Surgery, The University of Iowa, Iowa Health Care, Iowa City, Iowa, USA lucy-wibbenmeyer@uiowa.edu.ORCID 0000-0003-1424-069X

Funding

NCIPC CDC HHS R49 CE003095
6 · The paper itself

Abstract

introductionHousefires can cause devastating injuries, disproportionately affecting low socio-economic communities. Applying geographic information system and spatial analysis, we examined the association between housefires and socio-economic variables from the area deprivation index (ADI) and social vulnerability index.

methodsPatients who sustained a burn injury from a housefire and were admitted to our burn unit between 2008 and 2023 were identified from our burn registry. Spatial binary logistic regression estimated the associations between social vulnerability factors and census tract housefires.

resultsMultiple social vulnerability factors were associated with housefires with the final model, including fourth quartile of ADI (OR=5.9), percentage of black residents (OR=4.9) and mobile home residences (OR=2.5) compared with the first quartiles (p<0.05).

conclusionMultiple housefires occurring in a census tract are associated with social vulnerabilities. Identifying census tracts with higher ADI, black resident ratios and mobile home ratios can help focus community interventions on high-risk areas. Further studies are needed to evaluate and refine the model and determine the current model's predictive ability.

Indexed as

Built EnvironmentBurnsRural PopulationAdolescentAdultCensusesFemaleGeographic Information SystemsHumansMaleMiddle AgedNeighborhood CharacteristicsRisk FactorsSocial VulnerabilitySocioeconomic FactorsSpatial AnalysisBurnEpidemiologyGeographical / Spatial analysisPovertySocioeconomic Status

Identifiers

PMID40550634
PMCPMC12380116

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