A bivariate zero-inflated Poisson regression model to analyze occupational injuries

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journal

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Detail(s)

Original languageEnglish
Pages (from-to)625-629
Journal / PublicationAccident Analysis and Prevention
Volume35
Issue number4
Publication statusPublished - Jul 2003

Abstract

The aim of many occupational safety interventions is to reduce the incidence of injury. However, when measuring intervention effectiveness within a period, population-based accident count data typically contain a large proportion of zero observations (no injury). This situation is compounded where injuries are categorized in a binary manner according to an outcome of interest. The distribution thus comprises a point mass at zero mixed with a non-degenerate parametric component, such as the bivariate Poisson. In this paper, a bivariate zero-inflated Poisson (BZIP) regression model is proposed to evaluate a participatory ergonomics team intervention conducted within the cleaning services department of a public teaching hospital. The findings highlight that the BZIP distribution provided a satisfactory fit to the data, and that the intervention was associated with a significant reduction in overall injury incidence and the mean number of musculoskeletal (MLTI) injuries, while the decline in injuries of a non-musculoskeletal (NMLTI) nature was marginal. In general, the method can be applied to assess the effectiveness of intervention trials on other populations at high risk of occupational injury. © 2002 Elsevier Science Ltd. All rights reserved.

Research Area(s)

  • Bivariate Poisson, Excess zeros, Lost-time injury, Musculoskeletal, Participatory ergonomics team, Population-based count data