Socio-economic and demographic predictors of accidental dwelling fire rates

Chris Hastie, Rosalind Searle

Research output: Contribution to journalArticle

10 Citations (Scopus)
27 Downloads (Pure)

Abstract

Despite the considerable reduction in rates of fire that have been seen in the UK in recent years analysis of three years of service data from a large UK fire service reveals that there continue to be striking inequalities in the way in which fire is distributed through society. The use of principal component analysis (PCA) and ordinary least squares regression enabled the development of a model that explains around one third of the variance in rates of fire at small neighbourhood level using just three predictor variables: the proportion of residents identifying as Black, the proportion of residents who have not worked for more than five years or have never worked, and the proportion of single person households where the resident is aged under 65. The value of PCA in addressing problems of collinearity between potential predictor variables is particularly highlighted. The findings serve to update understanding of the distribution of fire in the light of the ongoing reduction in fire rates of recent years. They will help fire services to target fire safety interventions to those neighbourhoods and communities where they are most needed and have the greatest potential to bring about reductions in the rate of fire.

Publisher Statement: NOTICE: this is the author’s version of a work that was accepted for publication in Fire Safety Journal. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Fire Safety Journal, [84, (2017)] DOI: 10.1016/j.firesaf.2016.07.002

© 2017, Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/
Original languageEnglish
Pages (from-to)50-56
Number of pages7
JournalFire Safety Journal
Volume84
Early online date28 Jul 2016
DOIs
Publication statusPublished - Aug 2016

Keywords

  • Inequality
  • Principal component analysis
  • Linear regression
  • Race
  • Living alone
  • Unemployment
  • Fire
  • Prevention

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