An investigation of neighborhood-level social, economic and physical factors for railway suicide in Victoria, Australia

  • Lay San Too
  • , Matthew J. Spittal
  • , Lyndal Bugeja
  • , Allison Milner
  • , Mark Stevenson
  • , Roderick McClure

Research output: Contribution to journalArticlepeer-review

18 Citations (Scopus)

Abstract

Background: This study investigates the associations between railway suicide and neighborhood social, economic, and physical determinants using postcode-level data. It also examines whether the associations are influenced by having high concentration of high-risk individuals in a neighborhood area. Methods: Railway suicide cases from Victoria, Australia for the period of 2001-2012, their age, sex, year of death, usual residential address and suicide location were obtained from the National Coronial Information System. Univariate negative binomial regression models were used to estimate the association between railway suicide and neighborhood-level social, economic and physical factors. Variables which were significant in these univariate models were then assessed in a multivariate model, controlling for age and sex of the deceased and other known confounders. Results: Findings from the multivariate analysis indicate that an elevated rate of railway suicide was strongly associated with neighborhood exposure of higher number of railway stations (IRR=1.30 95% CI=1.16-1.46). Other significant neighborhood risk factors included patronage volume (IRR=1.06, 95% CI=1.02-1.11) and train frequency (IRR=1.02, 95% CI=1.01-1.04). An increased number of video surveillance systems at railway stations and carparks was significantly associated with a modest reduction in railway suicide risk (IRR=0.93, 95% CI=0.88-0.98). These associations were independent of concentration of high-risk individuals. Limitations: Railway suicide may be under-reported in Australia. Conclusions: Interventions to prevent railway suicide should target vulnerable individuals residing in areas characterized by high station density, patronage volume and train frequency.
Original languageEnglish
Pages (from-to)142-148
Number of pages7
JournalJournal of Affective Disorders
Volume183
DOIs
Publication statusPublished - 2015

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

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